What are the responsibilities and job description for the Gen AI platform Engineer position at DATAECONOMY?
GenAI Platform Engineer
Boston, MA
Full-time role
Experience: 10 yrs
About the Role
We''''''''re looking for a Senior GenAI Platform Engineer to build and operate our enterprise AI agent platform — hands-on, in the code, every day. This is an individual contributor role with no direct reports. You''''''''ll design and build durable asynchronous orchestration, RAG pipelines, and secure multi-agent workflows on AWS, working alongside a small team of peer engineers. You''''''''ll participate in architecture discussions and code reviews as a strong technical contributor, not as a manager.
Education & Experience
- Bachelor’s degree in computer science, Information Systems, Engineering, or equivalent practical experience.
- 5–8 years of professional software engineering experience.
- 2 years of hands-on experience building GenAI/Agentic AI applications in production.
What You''''''''ll Do
- Build AI agents and multi-agent workflows using Amazon Bedrock, Bedrock Agents, AgentCore, LangChain, and LangGraph.
- Design and implement RAG pipelines, prompt engineering strategies, and AI guardrails.
- Build backend services in FastAPI for agent submission, execution, lifecycle state machines, and status tracking.
- Implement queue-based dispatch and durable state stores, ensuring idempotency, retries, and failure recovery.
- Write Infrastructure as Code (Terraform) to provision and manage agent infrastructure on AWS.
- Integrate agents with vector databases, enterprise messaging systems, and internal workflow tools.
- Instrument services for observability — structured logging, tracing, metrics.
- Participate in code reviews and architecture discussions as a peer contributor.
- Write clear technical documentation (design docs, runbooks) for systems you build.
Required Qualifications
- Expert-level Python, with strong experience building REST APIs (FastAPI preferred).
- Hands-on experience with LLMs, Amazon Bedrock (Agents & AgentCore), LangChain, LangGraph, RAG, and vector databases.
- Strong experience with core AWS services: Lambda, ECS/EKS, API Gateway, S3, RDS/PostgreSQL.
- Working proficiency in Terraform and Docker.
- Experience with CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
- Solid understanding of asynchronous programming and event-driven architectures (Kafka or SQS).
- Experience with modern authentication patterns (OAuth2, OIDC, JWT) and AWS IAM.
Technical skills
- Programming: Python , FastAPI
- Generative AI: Amazon Bedrock, Bedrock Agents, AgentCore, LangChain, LangGraph, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Guardrails, Multi-Agent Systems
- Vector Databases: Pinecone, Amazon OpenSearch Vector Engine, FAISS, ChromaDB, pgvector
- Infrastructure as Code: Terraform, AWS CloudFormation (preferred exposure)
- Containers & Orchestration: Docker
- Databases: PostgreSQL, DynamoDB
- Event-Driven Architecture: Amazon SQS, Apache Kafka
- Authentication & Security: OAuth 2.0, OpenID Connect (OIDC), JWT, AWS IAM, Enterprise Identity Integration (Microsoft Entra ID)
- CI/CD & DevOps: Git, Automated Deployment Pipelines
- Observability: AWS Observability
- Software Engineering: System Design, Microservices Architecture, Backend Development, API Design, Code Reviews, Technical Documentation, Design Documents, Runbooks
- Development Practices: Unit Testing, Integration Testing, Code Quality, Secure Coding Practices, Agile/Scrum
Preferred Qualifications
- AWS Associate or Professional certification.