Current Jobs

Contract Type: Full-Time (40 hrs/week - long-term engagement) Location: 100% Remote – Mexico, India or Sri Lanka Experience: 5+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Data Infrastructure, or related engineering roles. 

Role Overview

We are seeking an experienced Databricks Platform Engineer to design, build, automate, and operate our enterprise Databricks Lakehouse platform on AWS. This role bridges Cloud Platform Engineering, Data Infrastructure, and Data Engineering, with a strong focus on infrastructure automation, security, governance, and standardization.  The ideal candidate will use Terraform and Infrastructure as Code (IaC) to deliver scalable and secure Databricks environments while establishing enterprise data governance through Databricks Unity Catalog. 

Key Responsibilities 

Infrastructure as Code & Platform Automation 

• Design, build, and maintain reusable Terraform modules for Databricks infrastructure across Development, Test, and Production environments. 
• Automate provisioning and lifecycle management of Databricks workspaces, compute resources, SQL warehouses, networking, security configurations, and storage integrations. 
• Manage IaC for AWS components including VPCs, security groups, IAM roles, private connectivity, and storage endpoints. 
• Develop and maintain CI/CD pipelines using GitHub Actions, GitLab CI, or similar platforms. 
• Implement deployment automation using Databricks Asset Bundles, Databricks APIs, Terraform, and related automation frameworks. 
• Establish reusable platform patterns and self-service "golden paths" for Data Engineering, Data Science, and Analytics teams. 

Unity Catalog & Data Governance 

• Design and implement the enterprise Unity Catalog architecture, including catalogs, schemas, volumes, storage credentials, and external locations. 
• Define governance standards that provide appropriate workload and team isolation while enabling secure data sharing and discoverability. 
• Implement and manage Role-Based Access Control (RBAC) and object-level permissions based on least-privilege principles. 
• Integrate Databricks access controls with enterprise identity and access management platforms. 
• Implement appropriate row-level and column-level security controls. 
• Establish data governance capabilities including lineage, auditing, classification, tagging, and access controls. 
• Automate governance policies through Terraform, APIs, and other platform automation mechanisms. 

Platform Operations & Security 

• Design and maintain compute and cluster policies to ensure standardized and secure platform usage. 
• Manage platform configuration, upgrades, capacity, and operational support. 
• Partner with AWS Cloud and Security teams to implement IAM controls, encryption, KMS integration, network security, and vulnerability remediation. 
• Troubleshoot Databricks platform, infrastructure, networking, access, and configuration issues. 
• Develop operational standards, architectural documentation, troubleshooting procedures, and platform runbooks. 

Required Skills & Qualifications 

• Experience: 5+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Data Infrastructure, or related engineering roles. 
• Databricks: Strong hands-on experience administering enterprise Databricks environments, including workspaces, compute, SQL warehouses, cluster policies, jobs, and platform security. 
• Unity Catalog: Practical experience designing and implementing Unity Catalog, including catalogs, schemas, external locations, storage credentials, permissions, and governance controls. 
• Terraform: Advanced experience developing reusable Terraform modules and managing Terraform state, providers, and multi-environment deployment patterns. 
• AWS: Strong hands-on experience with IAM, S3, VPC networking, security groups, KMS, and PrivateLink/private connectivity. 
• CI/CD: Experience developing automated deployment pipelines using GitHub Actions, GitLab CI, Jenkins, or equivalent platforms. 
• Automation: Experience with Databricks APIs, Databricks Asset Bundles, CLI tools, and infrastructure automation frameworks. 
• Programming: Proficiency in Python and SQL for automation, validation, and troubleshooting. 
• Security: Strong understanding of cloud security, identity management, least-privilege access, encryption, and secrets management. 

Preferred / Nice-to-Have Skills 

• Experience with additional AWS data services, such as DynamoDB, Redshift, Glue, Athena, and Kinesis. 
• Familiarity with Azure data services, such as Synapse Analytics, Data Factory, ADLS, Cosmos DB, and Microsoft Fabric. 
• Exposure to modern cloud data, streaming, analytics, and AI/ML services across AWS and Azure. 

ID: P24

Contract Type: Full-Time (40 hrs/week - long-term engagement) Location: 100% Remote – Mexico or India Experience: 8–10 years of overall IT experience, with 6+ years in DevOps, platform engineering, on prem and cloud-native infrastructure roles. 

Role Overview

Defines cloud platform strategy, drives engineering standards across DevSecOps, and leads the design of enterprise-scale infrastructure, security, and automation systems. This is a deeply technical and highly influential role — you will set the direction for how we build, secure, and operate cloud infrastructure at scale. You will be the go-to engineering authority for the most complex platform challenges. 

Core Responsibilities

• Infrastructure as Code (IaC): Own and evolve enterprise-wide IaC strategy using Terraform; establish standards for modularity, policy enforcement, drift management, and reusability across teams. 
• CI/CD Pipeline Architecture: Define and govern the CI/CD platform strategy; drive GitOps adoption, pipeline standardization, and developer experience improvements across all engineering teams. 
• Cloud Platform Strategy: Own the cloud architecture roadmap across AWS/Azure/GCP; drive decisions on multi-cloud strategy, landing zone design, cost optimization, and enterprise governance. 
• Containerization & Orchestration: Lead Kubernetes platform engineering (EKS/AKS), including cluster architecture, Helm chart standards, network policies, and long-term orchestration strategy. 
• Monitoring & Incident Response: Define the observability strategy — standardizing on tools, defining SLOs/SLAs, leading post-incident reviews, and driving proactive reliability improvements across the platform. 
• Security & Compliance: Own the DevSecOps security architecture: IAM governance, policy-as-code (OPA), OIDC federation, compliance automation, and security posture management at scale. 
• Teaming & Collaboration: Serve as technical anchor across engineering, security, and platform teams. Define DevOps engineering standards, mentor senior engineers, and represent the platform function in architecture and leadership forums. 

Experience (Must Have) 

• 8–10 years of overall IT experience, with 6+ years in DevOps, platform engineering, on prem and cloud-native infrastructure roles. 
• Proven track record of defining and owning on prem and cloud platform architecture and DevSecOps standards at enterprise scale. 
• Deep experience driving automation strategy across CI/CD, infrastructure provisioning, security, and operational workflows. 

Technical Skills (Must Have & Recent Experience) 

• OnPrem / Cloud (AWS/Azure) - compute, networking, storage, IAM, security services, and multi-cloud governance. 
• Containers: OnPrem Kubernetes implementation experience. Expert in Kubernetes platform engineering (EKS, AKS), Helm, service mesh (Istio/Linkerd), and container security.  
• IaC: Expert-level Terraform at enterprise scale; module design, policy enforcement, drift management, and state governance. 
• Configuration Management: Deep expertise in Ansible or similar; applies configuration management at scale with governance and auditability. 
• CI/CD: Expert across GitHub Actions, GitLab CI, Jenkins; GitOps tooling (ArgoCD, Flux); pipeline security and supply chain integrity. 
• Observability: Defines observability strategy using Prometheus, Grafana, CloudWatch, Azure Monitor; distributed tracing and SLO frameworks. 
• Programming: Strong Python/Node.js for complex automation, platform tooling, internal developer platforms, and AI-assisted infrastructure workflows. 
• Security: Expert in cloud IAM design, RBAC, OIDC federation, OPA, policy-as-code, zero-trust networking, and compliance automation. 

Soft Skills 

• Visionary and outcome-driven; able to translate business goals into platform strategy. 
• Strong design thinking and structured approach to complex, ambiguous problems. 
• Highly effective communicator with engineering peers, product leadership, and executive stakeholders. 
• Able to set technical direction, build consensus, and drive alignment across teams. 

Nice to Have 

• Deep background in multi-cloud or hybrid cloud platform design. 
• Experience with FinOps tooling and cloud cost governance at scale. 
• AI Exposure: Practical experience integrating GenAI tools (GitHub Copilot, Claude, etc.) into platform engineering workflows — infrastructure generation, runbook automation, incident analysis. 
• Experience building internal developer platforms (IDPs) with tools like Backstage or Port. 
• Open-source contributions to DevOps/platform tooling. 

ID: P23

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement) Location: 100% Remote – Anywhere in the U.S. Experience: 8–10 years of experience in SDET, quality engineering, or test architecture roles. 

Role Overview

We're looking for a Principal SDET to serve as the quality engineering anchor for our AI-first engineering organization. In this role, you'll define the long-term quality architecture, establish org-wide testing standards, and drive the strategy for how AI transforms quality engineering at scale. You'll work closely with Tech Leads, Principal Engineers, and product leadership to ensure our systems — including their GenAI components — meet the highest standards of reliability, correctness, and performance. 

Key Responsibilities

Quality & Test Engineering 

• Define and own the overall quality engineering strategy and test architecture across all product lines and engineering teams. 
• Establish org-wide standards, frameworks, and best practices for test automation, performance testing, and reliability engineering. 
• Lead the design of scalable, cloud-native test infrastructure on AWS, including containerized test environments and distributed test execution. 
• Drive quality governance: define KPIs, coverage targets, and quality gates across the SDLC. 
• Partner with Tech Leads and Principal Engineers to ensure testability is built into system and API designs from the start. 
• Lead the adoption of Agile quality practices; own sprint-level and release-level quality reporting to leadership. 
• Mentor senior and mid-level SDETs; develop engineering capability across the quality organization. 
• Evaluate, select, and champion testing tools and platforms — including AI-powered quality solutions. 

AI-Augmented Testing 

• Own the strategy for testing GenAI and LLM-powered systems at scale — including output validation, semantic similarity testing, hallucination detection, and behavioral regression. 
• Architect evaluation frameworks for LLM applications, defining metrics, benchmarks, and automated quality gates for AI features. 
• Partner with AI engineering teams to define testability requirements for LLM pipelines, RAG systems, and prompt frameworks. 
• Build and evolve monitoring and observability approaches for AI system quality in production. 
• Drive organization-wide adoption of GenAI tools to improve test productivity, coverage, and insight generation. 
• Represent quality engineering in AI architecture discussions, ensuring new AI systems are built with measurability and testability in mind. 

Candidate Requirements 

• 8–10 years of experience in SDET, quality engineering, or test architecture roles. 
• Deep expertise across the full spectrum of testing: functional, integration, API, performance, security, and reliability. 
• Proven track record of defining and owning test strategy and quality architecture across large engineering organizations. 
• Strong proficiency in Python, JavaScript, or Java; able to design and review complex automation systems. 
• Expert knowledge of CI/CD pipelines, cloud test infrastructure (AWS preferred), and containerized environments. 
• Experience leading quality initiatives across cross-functional teams and influencing engineering standards. 
• Strong communication and stakeholder management skills; able to present quality metrics and strategy to leadership. 
• Proven ability to mentor senior engineers and grow the capability of a quality engineering team. 

Good to Have 

• Experience designing evaluation frameworks for LLM or GenAI systems. 
• Background in MLOps, AI observability, or model quality monitoring. 
• Familiarity with chaos engineering and site reliability engineering (SRE) practices. 
• Experience with open-source contributions to testing frameworks or AI quality tooling. 
• Background in developer experience (DX) improvements that increase testability and code quality org-wide. 

ID: P22

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement) Location: 100% Remote – Anywhere in the U.S. Experience: 6+ years of professional Python development experience, including deploying Machine Learning or Generative AI applications.

Role Overview

We are looking for an experienced Python developer with a passion for Generative AI and hands-on expertise in cloud development. As a Senior GenAI Developer, you will lead the design, development, and deployment of scalable GenAI applications that redefine how professional services are delivered.     

Key Responsibilities:   

• GenAI Development: Build a platform to support enterprise GenAI solutions leveraging large language models (LLMs) and state-of-the-art frameworks.   
• Cloud Development: Design and implement robust, cloud-native solutions, preferably on Azure.   
• Full-Stack Contribution: Drive development from concept to deployment, ensuring seamless integration across back-end and front-end components.   
• Model Optimization: Fine-tune LLMs, enhance data retrieval from structured/unstructured sources, and optimize prompt engineering and agent plans.   
• Collaboration: Work closely with cross-functional teams, including domain experts and product managers, to deliver solutions aligned with business needs.   
• Mentorship: Guide and support junior developers to foster technical growth within the team.   
• Innovation: Stay ahead of emerging trends in AI and GenAI to continuously elevate our technical capabilities.     

Qualifications

• 6+ years of professional experience in Python development, including deploying machine learning or Generative AI applications.   
• 2+ years of hands-on experience building and deploying AI/ML solutions in Azure.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Advanced proficiency in Python and libraries such as PyTorch, Pandas, NumPy, or similar.
• Experience with Cloud development, preferably Azure (e.g., Azure App Service, Azure Functions, Azure Database Services, Azure AI services, and Azure Search).
• Experience with LLMs from OpenAI, Anthropic, Google, or Meta and their application in chatbots, RAG systems, and agents.
• Familiarity with GenAI frameworks like LangChain, Semantic Kernel, or equivalent tools.     

Soft Skills:   

• Excellent communication and collaboration skills in team-driven environments.   
• Analytical mindset with a strong focus on problem-solving.   
• Comfortable working in a fast-paced, dynamic startup culture.   
• Eagerness to learn and contribute to cutting-edge technologies.     

 Benefits   

• Competitive Compensation: Tailored to your experience and skill set.   
• Flexible Work Arrangements: 100% remote work for work-life balance.
• Career Growth: Opportunities for professional development and leadership roles.  
• Innovative Culture: Work on transformative technologies and make an impact in the AI space.  

ID: P01

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement) Location: Remote - Tamil Nadu, Karnataka, Pondicherry (India) + Sri Lanka (Colombo) Experience: 5–7 years of software engineering experience. 

Role Overview

We're looking for a Senior Software Engineer to play a key role in building and scaling our AI-powered enterprise software products. In this role, you'll own significant features end-to-end, contribute to architectural decisions, and help raise the bar across the engineering team. You'll bring deep full-stack expertise and hands-on experience building GenAI-powered applications — and you'll help define how AI becomes a native part of our engineering culture. 

Key Responsibilities 

Full Stack Development 

• Implement and own full-stack features using React.js, Next.js, and TypeScript on the frontend, with Python (FastAPI) and/or Node.js backends. 
• Design and build microservices and APIs that are scalable, secure, and maintainable. 
• Design and implement CI/CD pipelines for web and backend services. 
• Work with AWS-based infrastructure (Lambda, ECS, S3, etc.) and Docker/Kubernetes. 
• Contribute to infrastructure-as-code practices using Terraform. 
• Ensure system reliability, security, and cost optimization at the feature level. 
• Operate within an Agile delivery model, using Jira for planning, tracking, and reporting. 
• Conduct thorough code reviews and mentor junior engineers. 

AI Engineering 

• Build and optimize LLM pipelines from experimentation to production, including RAG systems. 
• Develop effective prompt engineering strategies for production use cases. 
• Conduct model evaluations and performance benchmarking. 
• Integrate GenAI features into core product workflows. 
• Contribute to CI/CD pipelines for AI systems. 
• Support monitoring and observability for LLM-powered features. 

Candidate Requirements 

• 5–7 years of software engineering experience. 
• Strong full-stack development skills using React.js, Next.js, and TypeScript. 
• Proficiency in Python (FastAPI) and/or Node.js for backend services. 
• Hands-on experience building and deploying LLM or GenAI applications in production. 
• Working knowledge of prompt engineering and RAG systems. 
• Solid knowledge of AWS (Lambda, ECS, S3, etc.), Docker, and Kubernetes. 
• Experience with CI/CD pipelines (GitHub Actions or similar). 
• Strong understanding of system design, API architecture, and microservices. 
• Experience working in Agile teams using Jira. 
• Proven track record of mentoring peers and conducting quality code reviews. 

Good to Have 

• Experience with fine-tuning or training LLMs. 
• Familiarity with LangChain, LlamaIndex, or similar frameworks. 
• Exposure to MLOps practices and model monitoring. 
• Experience with Terraform and infrastructure-as-code. 
• Contributions to open-source AI projects or experimentation frameworks. 

ID: P09

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement) Location: Remote - Tamil Nadu, Karnataka, Pondicherry (India) + Sri Lanka (Colombo) Experience: 5+ years in Quality Assurance roles, 3+ years of experience in Data Quality, Data Validation, ETL Testing, Data Warehouse Testing, or related Data Quality Engineering roles.

Role Overview

We are seeking a highly analytical and detail-oriented Senior SDET to ensure the quality, accuracy, and integrity of enterprise data solutions. The role will be responsible for validating data across the end-to-end data lifecycle, including data acquisition, integration, transformation, and storage. The engineer will work closely with Data Engineers, Solution Architects and Product Owners / Leads to ensure data products meet functional, business, and quality expectations. 

Key Responsibilities 

Quality & Test Engineering 

• Architect and own end-to-end test automation frameworks to validate data across ingestion, transformation, enrichment and consumption layers. 
• Define test strategies and quality standards for complex, cross-functional features and services. 
• Conduct thorough test design reviews and code reviews for automation code produced by the team. 
• Work closely with engineering leads to embed quality at the design and architecture stage. 
• Operate within an Agile delivery model; drive quality metrics, coverage reporting, and sprint-level test governance. 
• Mentor junior and mid-level SDETs; share knowledge and elevate the team's automation maturity. 

Test Planning & Execution 

• Execute functional, integration, regression, and data validation testing. 
• Ensure complete traceability between requirements and validation activities. 
• Use of AI-powered testing tool to develop test artifacts (Test Plan, Test Cases, Test Data etc) 

Defect Management & Root Cause Analysis 

• Identify, document, and prioritize data quality defects. 
• Partner with engineering teams to analyze root causes. 
• Validate corrective actions and remediation efforts. 

Key Deliverables  The successful candidate will be expected to produce: 

• Test Strategy and Validation Approach 
• Test Scenarios and Test Cases 
• Data Validation / Reconciliation Reports 
• Defect Analysis Reports 
• Release Quality Assessments 
• Data Quality Metrics and Dashboards 
• Quality Sign-off Recommendations 

Candidate Requirements 

• 5+ years in Quality Assurance roles 
• 3+ years of experience in Data Quality, Data Validation, ETL Testing, Data Warehouse Testing, or related Data Quality Engineering roles. 
• Strong understanding of data lifecycle management and data quality principles 
• Strong expertise in automation frameworks:  Pytest, or similar. 
• Deep experience with performance testing, and integration testing at scale. 
• Basic understanding of CI/CD pipelines and experience integrating tests into automated delivery workflows. 
• Familiarity with AWS or other cloud platforms for test infrastructure. 

Good to Have 

• Lead performance and load testing using tools like JMeter, k6, or Locust; analyze results and drive improvements. 
• Basic skills in Python, JavaScript - able to write production-quality automation code. 
• Exposure to chaos engineering or reliability testing practices. 
• Knowledge of security testing 
• Experience in environments using Cloudera / Databricks / Apache NiFi preferred 

ID: P08

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement) Location: Remote - Tamil Nadu, Karnataka, Pondicherry (India) + Sri Lanka (Colombo) Experience: 2–5 years of relevant Business Analysis / Product Ownership experience

Role Overview

We are looking for a Senior Business Analyst who combines strong requirements engineering fundamentals with hands-on process mapping and solutioning capability. This role owns the translation of business needs into clear, actionable, and technically feasible solutions — from requirement elicitation and process/workflow diagramming through documentation, Agile delivery, and UAT sign-off. The ideal candidate is equally comfortable running a stakeholder workshop, drawing a swimlane diagram of a broken process, and writing the user stories that fix it. 

Key Responsibilities 

• Elicit, analyze, and document business requirements through stakeholder interviews, workshops, and workflow observation. 
• Create and maintain current-state and future-state process flow diagrams and process maps (e.g., swimlane, BPMN-style) using tools such as Visio, Lucidchart, or Draw.io, to make workflows and handoffs explicit to both business and technical audiences. 
• Own solutioning: translate business problems into scalable, well-documented functional solution designs, working with Engineering to validate technical feasibility and implementation approach. \
• Author Business Requirement Documents (BRDs), Functional Requirement Documents (FRDs), user stories, acceptance criteria, and requirement traceability matrices. 
• Conduct gap analysis (as-is vs. to-be) and recommend process, workflow, or system improvements. 
• Participate in Agile ceremonies — sprint planning, backlog grooming/refinement, sprint review — and help prioritize requirements in partnership with Product Owners and Scrum teams. 
• Act as the primary liaison between business stakeholders and Engineering, QA, and UX teams; facilitate requirement walkthroughs and design reviews. 
• Define UAT scenarios, coordinate UAT execution with business users, and validate delivered features against acceptance criteria before release sign-off. 
• Support defect triage and root-cause discussions, ensuring solutions address the underlying process gap and not just the reported symptom. 
• Maintain documentation standards and contribute to process-quality initiatives (e.g., audit readiness, CMMI-aligned documentation) where applicable. 

Required Qualifications & Skills

• 2–5 years of experience as a Business Analyst, Product Owner, or in a comparable requirements/product role.
• Demonstrated, hands-on experience producing process flow diagrams and process maps using tools such as Visio, Lucidchart, or Draw.io — not just narrative process descriptions. 
• Proven solutioning experience — able to move from a business problem to a documented, technically validated solution design.
• Strong command of BRD/FRD authoring, user stories, and acceptance criteria (Given/When/Then or equivalent). 
• Working experience with Agile/Scrum delivery (sprint planning, backlog grooming); exposure to Kanban is a plus. 
• Strong stakeholder management and cross-functional collaboration skills across Engineering, QA, UX, and business teams. 
• Experience planning and coordinating UAT cycles. 
• Proficiency with requirement/project tracking tools such as Jira, Confluence, or Azure DevOps. 
• Bachelor's degree in Business, Engineering, Computer Science, or a related field, or equivalent practical experience. 

Preferred / Nice to Have 

• Domain experience in SaaS, B2B, Enterprise platforms, or ERP implementations.
• Exposure to process mining or analytics tools (e.g., Celonis) or data/reporting tools (SQL, Power BI). 
• Relevant certification: CBAP, CSPO, PMI-PBA, or equivalent. 
• Experience with API/integration-level solutioning (REST APIs, system integration design). 

What Success Looks Like 

Within the first 90 days, the Senior Business Analyst should be independently running requirement workshops, producing accurate process diagrams that both business and engineering trust, and contributing clean, implementation-ready BRDs/FRDs and user stories into active sprints — with visible ownership of at least one end-to-end process-improvement or solutioning initiative.  ID: P07

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement)  Location: Remote - Tamil Nadu, Karnataka, Pondicherry (India) + Sri Lanka (Colombo) Experience: 12+ YOE Overall, 5+ years of experience in Technical Project lead  

Role Overview

We are seeking a Technical Project Lead to lead and deliver full stack software projects.  This role requires a strong blend of agile delivery leadership, technical depth, and stakeholder (client, team etc.) management. You will work closely with clients, product owners, Tech Leads, full stack engineers and AI engineers to ensure timely, high-quality delivery of scalable, intelligent solutions. This role requires hands-on with Agile/Scrum practices, deeply understands modern web and GenAI architectures, and can bridge the gap between business objectives and technical execution.

Key Responsibilities (Must Have & Recent Experience ) 

• Serve as Project Lead for one or more cross-functional Agile teams, and own project planning and execution across all software development phases (Requirements, Architecture & Design, Development and Release) 
• Create and manage project plans, timelines, risk registers, and dependency tracking 
• Manage scope, schedule, and quality while balancing evolving product needs 
• Facilitate all Scrum ceremonies: Sprint Planning, Daily Standups, Reviews, and Retrospectives with adherence to Agile/Scrum principles, removing impediments and enabling continuous improvement 
• Act as the primary point of contact for internal and external stakeholders 

Deliverables (Primary) 

• Sprint deliverables aligned with delivery roadmap and release schedules 
• Sprint Reports (velocity, quality, predictability), RAID Log etc.  
• Post-release reviews and retrospective action items 

Required Qualifications / Experience 

• 12+ YOE Overall 
• 5+ years of experience in Technical Project lead  
• Proven track record delivering full stack cloud-based and/or AI/ML applications 
• Experience in Agile environments (Scrum, Kanban or hybrid models) 

Technical Skills 

• Strong understanding of full stack architectures  Front End (React/Angular) & Backend Technologies (Python, Node.js, Java, C#) 
• Cloud platforms: AWS / Azure/ GCP  
• DevOps tools: CI/CD pipelines, Docker, Kubernetes (foundation knowledge) 
• Experience with tools such as Jira, Azure DevOps, Confluence, GitHub/ GitLab 

 Soft Skills 

• Self Motivated, Excellent communication, facilitation, and negotiation skills 
• Strong problem-solving mindset with attention to detail 
• Ability to influence without authority &  to manage remote teams 
• Comfortable working in fast-paced, ambiguity-rich environments 

Preferred Qualifications 

• Background as a software engineer, tech lead or similar roles 
• Leverage AI for acceleration project planning & execution 
• Experience in regulated or enterprise-scale environments 
• Scrum Master Certification (CSM, PSM I/II, SAFe SM), PMP or PgMP certification 

ID: P18

Contract Type: Full-Time Contract (40 hrs/week - long-term engagement)  Location: Remote - Tamil Nadu, Karnataka, Pondicherry (India) + Sri Lanka (Colombo) Experience: 8–10 years of software engineering experience, including meaningful time in senior or lead roles.

Role Overview

We're looking for a Principal Engineer to serve as a technical anchor for our AI-first engineering organization. In this role, you'll drive the architecture and technical direction of our most complex systems, define engineering standards across the team, and ensure our AI-powered products are built to scale. You'll work closely with the Tech Lead and senior stakeholders to translate business goals into robust, forward-thinking technical solutions — while also being deeply hands-on when it matters. 

Key Responsibilities 

Full Stack Development 

• Lead the technical design of large-scale, cross-cutting full-stack initiatives. 
• Define and enforce engineering standards, patterns, and best practices across teams. 
• Implement full-stack features using React.js, Next.js, and TypeScript on the frontend, with Python (FastAPI) and/or Node.js backends. 
• Architect and oversee microservices, APIs, and service integration strategies. 
• Own and evolve AWS-based infrastructure for web and backend workloads, using Terraform for infrastructure as code. 
• Lead containerization and orchestration strategy using Docker and Kubernetes. 
• Drive system reliability, security architecture, and cost optimization across services. 
• Size and estimate projects across full-stack and AI workstreams; guide planning and prioritization. 
• Operate within an Agile delivery model, using Jira for planning and cross-team coordination. 
• Mentor senior and mid-level engineers; champion high engineering standards through code and design reviews. 

AI Engineering 

• Set the technical direction for GenAI development, including model selection, pipeline architecture, and scalability strategy. 
• Define and own best practices for LLM development, evaluation, and production deployment. 
• Architect end-to-end LLM pipelines from experimentation to production, including RAG systems and retrieval infrastructure. 
• Develop and standardize advanced prompt engineering frameworks across the team. 
• Lead rigorous model evaluations and define performance optimization strategies. 
• Design and oversee CI/CD pipelines tailored for AI systems. 
• Architect and maintain AWS-based infrastructure for AI workloads (SageMaker, etc.). 
• Build and evolve monitoring, observability, and evaluation tooling for LLM applications. 

Candidate Requirements 

• 8–10 years of software engineering experience, including meaningful time in senior or lead roles. 
• Deep full-stack development expertise using React.js, Next.js, and TypeScript. 
• Strong proficiency in Python (FastAPI) and/or Node.js for backend services. 
• Proven track record of building and deploying LLM or GenAI applications in production at scale. 
• Deep understanding of prompt engineering, LLM evaluation, and RAG systems. 
• Expert-level knowledge of AWS (SageMaker, Lambda, ECS, S3, etc.), Docker, and Kubernetes. 
• Strong experience with Terraform and CI/CD pipelines (GitHub Actions or similar). 
• Excellent background in system design, API architecture, distributed systems, and microservices. 
• Experience driving engineering standards, cross-team alignment, and technical decision-making. 
• Strong communication skills — able to influence technical direction with peers and leadership. 

 Preferred 

• Experience with fine-tuning, RLHF, or training LLMs. 
• Familiarity with LangChain, LlamaIndex, or similar frameworks. 
• Background in MLOps, model monitoring, and AI observability. 
• Experience with A/B testing and experimentation frameworks. 
• Open-source contributions or thought leadership in GenAI or distributed systems. 

ID: P05