Agentic AI Engineer
First seen by Alion on Sep 11, 2026.
Job Description:
Key Responsibilities :
- Design and develop AI agents and multi-agent systems for enterprise use cases.
- Build agentic workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI or similar technologies.
- Develop LLM-powered applications using OpenAI, Azure OpenAI, Gemini, Claude or equivalent models.
- Implement RAG pipelines using vector databases and enterprise knowledge sources.
- Integrate AI agents with APIs, databases, enterprise applications, search engines, and external tools.
- Develop agent capabilities including planning, reasoning, memory, tool calling, task decomposition, and decision-making.
- Build prompt engineering strategies and optimize LLM responses for accuracy and reliability.
- Work with Python to develop scalable AI services and backend applications.
- Implement evaluation, monitoring, guardrails, observability, and responsible AI practices.
- Fine-tune or customize models where required and optimize inference performance.
- Deploy AI solutions on AWS, Azure, or GCP using containers and CI/CD pipelines.
- Collaborate with Data Scientists, ML Engineers, Software Engineers, Architects, and business teams.
- Troubleshoot and improve the performance, scalability, security, and reliability of AI applications.
Required Skills :
- Strong programming experience in Python.
- Hands-on experience with Generative AI and Large Language Models (LLMs).
- Strong understanding of Agentic AI concepts and autonomous AI workflows.
- Experience with LangChain / LangGraph / AutoGen / CrewAI or similar frameworks.
- Strong knowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval.
- Experience with prompt engineering and LLM orchestration.
- Experience integrating REST APIs, tools, function calling, and enterprise systems.
- Knowledge of FastAPI, Flask, or similar Python frameworks.
- Experience with databases such as PostgreSQL, MongoDB, SQL Server or similar.
- Experience with vector databases such as Pinecone, FAISS, Chroma, Weaviate, Milvus or equivalent.
- Understanding of ML/AI lifecycle, model evaluation, monitoring, and deployment.
- Good understanding of cloud platforms such as AWS, Azure, or GCP.
Skills
Python, Generative AI, LangChain, Prompt Engineering, FastAPI, AWS, LangGraph, OpenAI