Current Jobs

Contract Type: Full-Time (40 hrs/week - long-term engagement) Location: 100% Remote – Mexico, India or Sri Lanka Experience: 8+ years of hands-on experience in delivering data engineering solutions

Required Skills & Qualifications 

• Experience in analyzing, identifying automation opportunities in a Data Platform modernization project – including accelerating ingestion frameworks, transformation stage, data quality and metadata. 
• Experience leading a team of 5+ team members, responsible for technical solution, design review, code reviews and mentoring 
• Strong hands-on experience in AWS/Azure, with experience in data engineering related services and technologies like Databricks / Cloudera / Snowflake (Prior deep experience with Cloudera is an added advantage) 
• Expertise in database concepts, SQL and relational modelling 
• Good understanding and experience working with NoSQL databases 
• Strong hands-on experience in implementing data pipelines using Python, Scala and PySpark 
• Good understanding of data lake and data warehouse concepts, modern data architecture patterns and industry trends in data engineering space 
• Good understanding and experience implementing data quality management solutions 
• Good understanding of metadata management for data engineering solutions and data platforms 
• Good understanding of data governance concepts – including data stewardship, data security and data privacy management 
• Experience with version control tools like Git for managing version control for source code 
• Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solution components 
• Strong analytical and problem-solving skills 
• Excellent communication and collaboration skills 

Responsibilities: 

• Lead technical design efforts for data engineering solution components, automation and accelerators 
• Design and implement scalable, secure and resilient data engineering solutions on AWS/Azure, with a good understanding of data architecture patterns 
• Evaluate and select appropriate technology stack for data engineering solution components – cloud native services, open-source tools, data storage, data processing frameworks etc 
• Lead, mentor and manage a team of dynamic data engineers for development, testing and implementation of data pipelines ensuing quality, performance and on-time delivery 
• Responsible for detailed technical design and data mapping specification 
• Ensure adherence to industry best practices, coding standards and guidelines driving continuous improvement in code quality and delivery excellence 
• Optimize data solutions for performance, cost-efficiency and scalability 
• Ensure data quality and integrity for downstream systems and applications 
• Plan, prioritize and manage data engineering projects, ensuring timely delivery with quality 
• Identify and mitigate risks, troubleshoot issues, handle customer escalations 
• Ensure alignment with business requirements and priorities, working closely with stakeholders – both internal and customer 
• Maintain comprehensive technical documentation, including architecture diagrams, high level / low level data integration design, data mapping specifications, database design etc 
• Working closely with peers, BI engineers and data scientists to enable advanced analytics, machine learning models and reporting solutions 

ID: P28

Contract Type: Full-Time (40 hrs/week - long-term engagement) Location: 100% Remote (Based in USA, Canada, Mexico, India or Sri Lanka) Experience: 10+ years as a product owner or equivalent  

Core responsibilities 

Product ownership and backlog 

• Own a single prioritized backlog spanning ingestion, Bronze/Silver/Gold build, stored-procedure conversion, semantic and ontology work, and data quality. 
• Translate business outcomes into epics, user stories and acceptance criteria that engineers can build against and QA can test against. 
• Set and defend priority order - by business value, dependency and risk - and make trade-offs explicit when scope, date and quality collide. 
• Maintain a rolling 2–3 sprint ready backlog per pod; accept or reject completed work against acceptance criteria. 

Requirements and rationalization 

• Run the rationalization deliverable to a concrete definition: what percentage of reports and procedures counts as “done”, what evidence supports the cut, and who signs off. 
• Lead the bottom-up, usage-based approach - present each line of business with “here is your world, here are your top 25 reports” and take confirmation, rather than open requirements gathering across 1,600 users. 
• Own the current-state to target-state mapping: which flows map to Bronze, Silver and Gold, and which legacy artefacts are retired rather than converted. 

Technical depth 

• Work fluently with engineers on medallion design, conformance rules, SCD handling, data contracts, schema evolution and lineage. 
• Understand the stored-procedure conversion approaches well enough to prioritize them: AI-assisted generation, parser/rule-based (SQLGlot, ANTLR, Calcite), template-based for repeated patterns, and manual re-engineering for tightly coupled logic. 
• Drive the early proof: convert one simple, one medium and one complex procedure end to end (analyse, design, convert, test), bucket the remainder by similarity, and use the results to size the factory. 
• Own the definition of done for data assets: reconciliation passed, data quality expectations met, lineage captured, documentation published. 

Validation and quality 

• Define validation criteria up front with each line of business - the reports, balances and metrics that must reconcile before sign-off - so nothing surfaces for the first time at UAT. 
• Own source-to-target reconciliation and parallel-run acceptance with QA; ensure audit balance controls and data quality expectations are specified as requirements, not retrofitted. 
• Serve as the business-facing owner for defect triage and prioritization during migration and hypercare. 

Stakeholder engagement 

• Act as the standing interface between LoB champions and the pods; run backlog reviews, demos and release communications. 
• Sequence visible early value - semantic model and natural-language access for one LoB - to sustain business confidence during a multi-year build. 

Qualifications  

• 10+ years as a product owner or equivalent  
• Demonstrated experience migrating or modernizing a legacy warehouse, including large-scale logic conversion and parallel-run validation. 
• Practical grounding in dimensional modelling, semantic layers, and ideally ontology or knowledge-graph concepts. 
• Strong written specification skills: acceptance criteria that are testable, unambiguous and traceable to a business outcome. 
• Comfortable saying no to scope, and credible enough technically that engineers and business stakeholders both accept the answer. 
• Insurance or regulated-industry data experience preferred; CSPO, PSPO or equivalent an advantage. 

ID: P26

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.  
• Infrastructure & Business Continuity: Experience with Nutanix architecture, Kubernetes control-plane setup, DNS and routing, secrets management, business continuity planning (BCP), and backup and restore strategies. 
• 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: 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: 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