Senior AI Engineer - RAG/LLM

Role Summary :

We are looking for Senior AI Engineers with strong handson expertise in Generative AI on AWS, specifically AWS Bedrock and agent-based AI architectures. The role involves designing and building productiongrade 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 (plannerexecutor, toolcalling 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 (NonNegotiable) :

• 7 to 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 toolusing LLM workflows

• Solid experience with Python for GenAI development

• Handson 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 :

• Handson AWS Bedrock implementation (real project experience, not learning/demo)

• Agentic AI / LLM agents / toolcalling workflows

• RAG architectures + vector databases