Job Summary

This role demands an experienced Agentic AI Developer to design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing complex, multi-step workflows within a fast-paced, agile environment.

Responsibilities

- Design, develop, and test autonomous AI agents and multi-agent systems to solve complex business problems.

- Write clean, scalable, and maintainable production-grade code using Python.

- Deploy, manage, and scale AI architectures and agentic workflows securely on Google Cloud Platform (GCP).

- Integrate Large Language Models (LLMs) with external APIs, cloud databases, and enterprise software toolchains.

- Build and optimize advanced Retrieval-Augmented Generation (RAG) pipelines and manage vector databases.

- Implement robust evaluation frameworks, strict grounding techniques, and anti-hallucination guardrails to ensure enterprise-grade reliability.

- Monitor agent performance, debug complex AI reasoning loops, and optimize systems for latency and cost.

- Collaborate closely with product managers, data engineers, and stakeholders to translate business requirements into technical AI solutions.

Required Skills

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence,



Software Engineering, or a related technical field.

- Proven hands-on experience building and deploying generative AI applications in a production environment.

- Advanced proficiency in Python programming with 7-9 years of experience, including asynchronous programming and API development.

- Experience with GCP services, specifically Vertex AI, Google ADK, Cloud Run, Cloud Functions, and BigQuery.

- Deep understanding of LLM capabilities, advanced prompt engineering, and context window management.

- Practical experience with Gen AI orchestration and agentic frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI.

- Robust foundational knowledge of vector search technologies, embeddings, and semantic search methodologies.

Desirable Skills

- Experience designing complex multi-agent architectures where AI models collaborate to solve tasks.

- Background in implementing MLOps pipelines, CI/CD for machine learning, and automated model evaluation.

- Solid understanding of data security, privacy compliance, and AI governance best practices.

- Experience with containerization technologies like Docker and Kubernetes.

📌 Consultant - Python Agentic AI (Chennai)
🏢 enGen Global
📍 Chennai