Description

Job Summary

We are seeking a highly skilled Senior AI / Agentic AI Engineer with strong hands-on experience building and deploying production-grade Generative AI and Agentic AI solutions.

The ideal candidate will have 2+ years of hands-on AI engineering experience with demonstrated expertise in AI Agents, LLMs, RAG, Prompt Engineering, Python, APIs, cloud platforms, and security.

Candidates must be able to demonstrate at least one complete production AI solution covering the full lifecycle from retrieval and tool execution through evaluation, deployment, and monitoring.

Key Responsibilities

•              Design, develop, and deploy production-grade Agentic AI and Generative AI solutions.

•              Build AI agents capable of reasoning, retrieval, orchestration, and tool/API execution.

•              Develop and optimize RAG (Retrieval-Augmented Generation) architectures.

•              Work extensively with LLMs, prompt engineering, context management, and AI workflows.

•              Develop AI applications and services using Python and APIs.

•              Integrate AI solutions with enterprise applications, data platforms, databases, and external services.

•              Design and implement evaluation frameworks to measure AI quality, accuracy, reliability, and performance.

•              Deploy AI solutions into production cloud environments.

•              Implement appropriate security, monitoring, logging, and operational controls for production AI systems.

•              Collaborate with engineering, data, product, and business teams to translate business requirements into scalable AI solutions.

Required Qualifications

•              2+ years of hands-on AI engineering experience.

•              Strong hands-on experience with Agentic AI / AI Agents.

•              Strong understanding of Large Language Models (LLMs).

•              Hands-on experience with RAG architectures.

•              Strong Prompt Engineering experience.

•              Strong programming skills in Python.

•              Experience developing and integrating APIs.

•              Experience deploying AI applications in cloud environments.

•              Understanding of security considerations for enterprise AI applications.

•              Proven experience taking AI solutions from development into production.

Critical Requirement

Candidates must be able to demonstrate at least one end-to-end production AI solution involving:

Retrieval → Agent/Tool Execution → Evaluation → Deployment → Monitoring

The candidate should be able to clearly explain their individual contribution, architecture decisions, technologies used, production deployment, and how the solution was evaluated and monitored.

Key Skills

Education

Any Graduate