We are seeking an experienced AI Engineer with 5+ years of software engineering experience and 2+ years of hands-on expertise in building Agentic AI applications, LLM-powered solutions, and intelligent workflow automation. The ideal candidate will have strong Python development skills and experience designing enterprise AI solutions using modern LLM frameworks, retrieval-augmented generation (RAG), vector databases, and multi-agent architectures.
This role involves designing, developing, and deploying scalable AI applications that automate business processes, integrate with enterprise systems, and leverage autonomous AI agents to improve productivity and decision-making.
Key Responsibilities
- Design and develop enterprise AI applications using Python and cloud-native architectures.
- Build intelligent AI agents and multi-agent systems capable of reasoning, planning, tool usage, and autonomous task execution.
- Develop GenAI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
- Design and implement agent orchestration workflows using modern AI frameworks such as LangGraph, LangChain or similar technologies.
- Develop AI-powered assistants, copilots, and workflow automation solutions for enterprise business processes.
- Build and maintain knowledge retrieval systems, embedding pipelines, semantic search, and contextual memory for AI applications.
- Integrate AI agents with enterprise applications, REST APIs, databases, messaging systems, and third-party services.
- Design secure and scalable APIs and microservices to support AI applications and agent workflows.
- Optimize prompt engineering, context management, memory strategies, and tool selection to improve AI response quality.
- Evaluate, benchmark, and integrate commercial and open-source LLMs based on business requirements.
- Implement observability, monitoring, logging, evaluation, and guardrails for production AI systems.
- Collaborate with product managers, architects, and engineering teams to translate business requirements into scalable AI solutions.
- Deploy and manage AI applications on AWS, Azure, or GCP using modern DevOps and CI/CD practices.
Required Qualifications
- 5+ years of software engineering experience with strong Python programming skills.
- 2+ years of hands-on experience building AI applications using Large Language Models
- Strong experience with Agentic AI concepts, autonomous agents, AI orchestration, and workflow automation.
- Experience with AI frameworks such as LangGraph, LangChain or similar.
- Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
- Experience with embeddings, semantic search, vector databases, and knowledge retrieval systems.
- Experience working with vector databases such as Pinecone, Milvus, Weaviate, Chroma, Redis Vector, FAISS, OpenSearch, or similar.
- Strong experience building REST APIs using FastAPI, Flask, or similar Python frameworks.
- Experience integrating AI applications with enterprise systems through REST APIs, GraphQL, messaging platforms, or event-driven architectures.
- Experience with Docker, Kubernetes, Git, GitHub Actions, and CI/CD pipelines.
- Experience deploying cloud-native applications on AWS, Azure, or Google Cloud Platform.
- Strong understanding of distributed systems, microservices, asynchronous programming, and event-driven architectures.
- Experience implementing authentication, authorization, and secure AI application design.
- Strong debugging, performance tuning, and production support experience for AI applications.
Preferred Qualifications
- Experience with Model Context Protocol (MCP) servers and tool integration.
- Experience with AI evaluation frameworks, observability platforms, and LLM monitoring tools.
- Knowledge of prompt optimization, guardrails, hallucination mitigation, and AI safety best practices.
- Exposure to AI-assisted software development tools such as GitHub Copilot, Cursor, Claude Code, or similar.