Engineering Manager

Key Responsibilities
Lead, coach, and manage a team of ~10 engineers, including backend, AI/ML, and cloud engineers.
Drive execution of product development initiatives from design to deployment.
Conduct performance reviews, support hiring initiatives, and foster a culture of ownership and engineering excellence.

GenAI & Agentic AI Development
Implement and enhance Agentic AI architectures using Strands, LangGraph, and autonomous agent patterns.
Build and optimize RAG-based systems, enterprise knowledge engines, and multimodal LLM pipelines.
Evaluate and leverage appropriate foundation models such as Gemini, GPT, Claude, Opus 4.6 based on use case fit.

Guardrails, Safety & Responsible AI
Design, implement, and continuously refine LLM guardrails, including:

Input/output filtering
Content moderation
Hallucination reduction strategies
Response validation

Lead hands-on architecture and development on AWS using services such as Lambda, S3, DynamoDB, API Gateway, Step Functions, ECS/EKS

Technical Execution & Collaboration
Contribute to system architecture, code reviews, and design decisions.
Build scalable microservices and AI integration layers using Python (FastAPI preferred).
Work cross-functionally with Product, QA, DevOps, and CloudOps teams to deliver enterprise-grade AI solutions.

Required Skills & Experience
Technical Expertise

10+ years in software engineering and product development.
Proven experience managing 10+ engineers.
Hands-on experience with:
Agentic AI frameworks: Strands, LangGraph
Amazon Bedrock and multimodel integrations
RAG pipelines, embeddings, vector databases
Python (advanced proficiency) and microservices
AWS Cloud architecture and development
Strong understanding of major LLM families: Gemini, GPT, Claude, Opus 4.6.