GenAI Engineer
First seen by Alion on Oct 1, 2026.
Role : Agentic AI / GenAI Engineer - GCP
We are looking for an experienced Agentic AI / GenAI Engineer to design, develop, and deploy production-grade AI solutions using LLMs, RAG, and agentic AI technologies. The ideal candidate should have strong hands-on experience in Python, GenAI/LLM application development, RAG architectures, and GCP.
Key Responsibilities :
- Design and develop scalable AI/ML solutions using LLMs and GenAI frameworks.
- Build production-grade LLM-powered applications and AI agents.
- Develop backend services and APIs using Python, FastAPI/Flask.
- Implement RAG pipelines including ingestion, chunking, embeddings, retrieval, and evaluation.
- Work on prompt engineering, tool/function calling, structured outputs, and hallucination control.
- Deploy and monitor AI solutions using MLOps/LLMOps practices.
- Implement LLM security, guardrails, PII protection, and prompt-injection prevention.
- Collaborate with cross-functional teams to design and deliver end-to-end AI solutions.
Mandatory Requirements :
- 6+ years of experience in AI/ML, Data Science, or Software Engineering.
- 3+ years of hands-on experience in GenAI, LLMs, RAG, or Conversational AI.
- Strong programming skills in Python.
- Hands-on experience with FastAPI / REST APIs / asynchronous processing.
- Strong experience in RAG implementation and vector databases.
- Understanding of embeddings, vector search, prompt engineering, and LLM evaluation.
- Experience with LLM security and guardrails.
- Experience with one or more agent/GenAI frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen.
- GCP - Mandatory.
- Hands-on experience with Google Cloud Platform (GCP) is mandatory.
- Experience with Vertex AI / Gemini or equivalent GCP AI platforms.
- Experience deploying applications using Cloud Run, GKE, or similar GCP services.
Good to Have :
- Google Agent Development Kit (ADK).
- Gemini Enterprise / Agent Engine.
- RAGAS, Evals, or custom evaluation pipelines.
- Model monitoring and observability.
- Multi-agent architecture.
- Human-in-the-loop workflows.
- Knowledge graph or enterprise search integration.
What We're Looking For :
- Strong problem-solving and analytical skills.
- Ability to take AI solutions from prototype to production.
- Experience working in Agile environments.
- Strong communication and collaboration skills.
Skills
Python, Generative AI, LangChain, FastAPI, Vertex AI, RAG, Google Cloud Platform, Artificial Intelligence, Agentic AI, LLM, Conversational AI