About the role
Job Post Date: 19/08/2026 Job Expiry Date: 01/12/2026 Location: Pune [India] Domain: IT Total Experience: 7.00 to 15.00 Years No of Openings: 1 We have a demand for a Contractor on the SCBU EDA Agent Enablement team for a Contractor with around 10 plus years experience. Qualifications: Bachelor’s Degree in Computer Science/Engineering, Informatics, or a related technical field 9 13 years of experience in developing solutions for analytics use cases. Technical Skills – Contractor (Agent Enablement) Agent Development & Frameworks Hands on experience designing, building, and deploying AI agents on a public cloud ecosystem (AWS preferred) Working knowledge of agentic frameworks – LangGraph, CrewAI, Strands Agents SDK (multi agent orchestration, tool calling, state/memory management) Experience with the Model Context Protocol (MCP) or similar tool/context integration patterns Experience building RAG pipelines – embeddings, vector databases/knowledge bases (e.g., OpenSearch, Bedrock Knowledge Bases), chunking/retrieval strategies Cloud & Platform Proficiency with AWS AI/ML services – Bedrock, SageMaker, Bedrock AgentCore Familiarity with the AWS Well Architected Framework (Generative AI Lens) Working knowledge of IAM/least privilege permissions for agent tool access and secrets management Engineering & DevOps Hands on Python scripting CI/CD practices and Infrastructure as Code, specifically AWS CDK Comfort with containerization/serverless deployment patterns (Docker, Lambda) for agent runtimes Git/version control fundamentals Operations & Quality Experience incorporating Human in the Loop (HITL) checkpoints into agent workflows Experience with agent monitoring, observability, and tracing (e.g., CloudWatch, OpenTelemetry, LangSmith style tracing) Experience with agent evaluation/testing – regression testing of prompts, benchmarking agent output quality Familiarity with Gen AI assisted coding tools (GitHub Copilot, Claude Code) and how to integrate them into a dev workflow LLM Foundations Core Gen AI, LLM concepts: temperature, Top P, Top K, context window/token limits, prompt engineering fundamentals Awareness of function/tool calling and structured output patterns Responsible AI Awareness of ethical and responsible AI use, including AWS Bedrock Guardrails, PII redaction, and content filtering
