- Design and develop Agentic AI solutions for enterprise-level use cases.

- Build and deploy AI/ML applications using modern frameworks and tools.

- Develop scalable APIs using FastAPI (Python-based services).

- Implement agent orchestration frameworks such as :

1. LangGraph.

2. LangChain.

3. Crew AI.

- Work on cloud-based AI/ML infrastructure (AWS / Azure / GCP).

- Integrate AI solutions with internal and external enterprise systems & data platforms.

- Implement observability, monitoring, and guardrails for AI solutions.

- Ensure auditability and explainability (XAI) across solutions.

Technical Skills Required :

Core Skills :

- Strong programming experience in Python.

- Hands-on with LLM-based applications / Agentic AI systems.

- API development using FastAPI.

AI/ML & Frameworks :

Experience with :

- LangChain / LangGraph / Crew AI.

- Exposure to model evaluation frameworks.

Cloud & Infrastructure :

Strong understanding of :

- AWS / Azure / GCP.

- AI/ML infrastructure design and deployment.

DevOps & Deployment :

- CI/CD pipeline implementation.

Experience with :

- Docker / Kubernetes / Containerization.

- Building scalable and reliable deployments.

AI Engineering Tools :

Familiarity with AI coding assistants such as :

- GitHub Copilot.

- Codex.

- Claude Code.

Additional Skills :

- Experience with MCP servers & tools.

Knowledge of :

- Observability frameworks.

- Responsible AI (guardrails, safety layers).

Good to Have :

- Experience in enterprise AI integration environments.

- Understanding of data ecosystems and API-first architectures.

- Exposure to regulated industry environments (auditability focus).