- Hands-on Experience: Proven track record in building and deploying AI agents using frameworks such as LangChain, Strands, or cloud-native ADKs (Agent Development Kits).
- CSP Foundation Models: Practical experience working with major Cloud Service Provider (CSP) AI ecosystems (e.g., AWS Bedrock, Google Vertex AI, Azure OpenAI Service).
- Agent Capabilities: Deep knowledge of agentic architecture patterns (ReAct, multi-agent coordination, tools/function calling, memory retention, and RAG architectures)
- Multi-Cloud Exposure: Hands-on experience navigating and deploying into at least one primary cloud provider (AWS, GCP, or Azure), with general operational knowledge across a multi-cloud estate.
- Infrastructure as Code (IaC): Proficient in writing modular, reusable Terraform scripts for cloud infrastructure management.
- DevOps Practice: Experience configuring CI/CD pipelines (e.g., GitHub Actions, GitLab CI, Azure DevOps, Jenkins) for both standard application code and AI/ML artifacts.
- Problem Solver:



Proven ability to rapidly build POCs from rough business requirements to prove technical feasibility.
- Collaborative Team Player: Excellent communication skills with a track record of actively collaborating with competency centers, engineering leads, and business teams.
- Experience with vector databases (e.g., Pinecone, Qdrant, PGVector, Milvus).
- Familiarity with Docker, Kubernetes, or serverless execution models (AWS Lambda, Azure Functions, Cloud Run) for lightweight agent hosting.
- Exposure to agent monitoring, evaluation frameworks, and LLM observability tools
- Core Languages: Robust proficiency in Java or .NET (C#) for writing core enterprise service layers and microservice
- SDLC Discipline: Full-lifecycle experience, including system design, unit testing, automated integration testing, and code reviews.

📌 Lead Software Engineer (Chennai)
🏢 Virtusa
📍 Chennai