Job Summary :

We are looking for a hands-on AI Engineer to design, develop and deploy enterprise-scale Generative AI and Agentic AI solutions. The role involves building AI agents, LLM applications, RAG pipelines, API integrations and intelligent workflow automations for enterprise use cases.

Key Responsibilities :

- Design, develop and deploy AI Agents / Agentic AI solutions from concept to production.

- Build GenAI/LLM applications, RAG pipelines and intelligent automation workflows.

- Develop AI services and integrations using Python, FastAPI/REST APIs and enterprise systems.

- Implement LangChain, LangGraph or similar AI orchestration frameworks.

- Integrate LLMs with APIs, enterprise applications, databases and external tools using tool/function calling.

- Develop scalable, secure and reliable AI solutions for production environments.

- Perform AI evaluation, testing, debugging, monitoring and optimization.

- Implement appropriate AI guardrails, security, privacy and responsible AI practices.

- Work with cloud platforms such as AWS, Azure or GCP.

- Follow software engineering best practices including Git, CI/CD, testing, documentation and code reviews.

- Collaborate with product, engineering and business stakeholders to translate requirements into technical solutions.

Required Skills :

- 9+ years of overall software engineering experience.

- 2+ years of hands-on GenAI / Agentic AI experience.

- Strong hands-on Python development.

- Strong experience with AI Agents / Agentic AI.

- Experience with RAG / Retrieval-Augmented Generation.

- Strong knowledge of LLMs / Generative AI.

- Hands-on experience with LangGraph / LangChain.

- Experience with tool calling / function calling / API integrations.

- Strong experience developing REST APIs / FastAPI.

- Experience deploying AI solutions into production environments.

- Strong software engineering fundamentals : coding, testing, debugging, Git and deployment.

Preferred Skills :

- MCP / Multi-Agent Systems.

- LLM evaluation and observability.

- AI guardrails / Responsible AI.

- Vector databases.

- Docker / Kubernetes / CI/CD.

- AWS / Azure / GCP.

- Experience building enterprise AI platforms or workflow automation.

Who We're Looking For :

Candidates who have personally designed and implemented AI solutions end-to-end from architecture and development through integrations, testing/evaluation, deployment and production support.