Role Title: Senior AI Engineer – Generative AI (AWS Bedrock & Agentic Systems)
Experience: 7–12 years
Location: India (Remote)
Notice Period:Immediate to 15 days only
Role Summary
We are looking for Senior AI Engineers with strong hands‑on expertise in Generative AI on AWS, specifically AWS Bedrock and agent-based AI architectures. The role involves designing and building production‑grade AI agents, RAG systems, and orchestration workflows that integrate with enterprise applications.
Key Responsibilities
- Designed and developed Generative AI applications using AWS Bedrock, integrating foundation models such as Claude, LLaMA, Titan, etc.
- Built agentic AI systems (planner–executor, tool‑calling agents, multi-agent workflows) to automate complex business processes
- Implemented RAG pipelines using vector databases (OpenSearch, Pinecone, FAISS, etc.) and enterprise data sources
- Developed prompt engineering strategies, guardrails, and evaluation frameworks for accuracy, safety, and cost optimization
- Integrated AI agents with AWS services such as Lambda, API Gateway, Step Functions, DynamoDB, S3
- Ensured security, privacy, and compliance (IAM, data masking, encryption, model access controls)
- Optimized inference latency and token usage; monitored production workloads and cost metrics
- Collaborated with MLOps/Platform teams to support CI/CD, monitoring, and scalable deployments
- Acted as a senior technical contributor, guiding juniors and reviewing GenAI solution designs
Must‑Have Skills (Non‑Negotiable)
- 7–12 years of overall software/AI engineering experience
- Strong hands‑on experience with AWS Bedrock in real projects (not PoC-only exposure)
- Proven experience building agentic AI or tool‑using LLM workflows
- Solid experience with Python for GenAI development
- Hands‑on experience with RAG architectures, embeddings, and vector stores
- Strong AWS fundamentals: IAM, networking basics, serverless services
- Clear understanding of GenAI risks, hallucination management, prompt controls
Good‑to‑Have Skills
- Experience with frameworks like LangChain, LlamaIndex, Semantic Kernel
- Exposure to enterprise domains such as BFSI, healthcare, insurance, or pharma
- Experience in model evaluation, benchmarking, and observability
- Prior experience working on customer-facing or production AI platforms
Mandatory Skills:
- Hands‑on AWS Bedrock implementation (real project experience, not learning/demo)
- Agentic AI / LLM agents / tool‑calling workflows
- RAG architectures + vector databases
- Strong Python background
