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

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