Senior AI Engineer – Generative AI (AWS Bedrock & Agentic Systems)

Job description

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