Agentic AI/Generative AI Engineer - Data Science
First seen by Alion on Aug 21, 2026.
Agentic AI / GenAI Engineer (Data Scientist)
Location : Remote
Experience :
6+ years in AI/ML/Data Science/Software Engineering, including at least 3 years of hands-on experience in Generative AI, LLMs, RAG systems, or conversational AI.
Role Overview :
We are seeking a highly skilled Agentic AI / GenAI Engineer (Data Scientist) to design, develop, and deploy production-grade AI systems. The ideal candidate will have strong expertise in building LLM-powered applications, implementing Retrieval-Augmented Generation (RAG), and deploying scalable AI solutions on cloud platforms such as Google Cloud.
Key Responsibilities :
- Design and build scalable AI/ML solutions using LLMs and GenAI frameworks
- Develop APIs and backend services using Python (FastAPI/Flask)
- Implement RAG architectures including ingestion, chunking, embeddings, retrieval, and evaluation
- Work on prompt engineering, tool/function calling, and structured outputs
- Deploy and monitor AI models using MLOps/LLMOps practices
- Ensure security, governance, and compliance (PII handling, prompt injection prevention, data leakage control)
- Build production-ready systems and real-world AI applications
- Collaborate with cross-functional teams for solution design and delivery
Mandatory Skills :
Core Technical Skills :
- Strong programming skills in Python
- Experience with FastAPI, REST APIs, async processing
- Hands-on experience in LLM application development
- Strong understanding of:
1. Embeddings & vector search
2. Prompt design & evaluation
3. Hallucination control techniques
- Experience in RAG implementation using vector databases
- Knowledge of LLM security & guardrails
Cloud & Platform Skills (GCP MUST):
- Experience with Vertex AI / Gemini or equivalent platforms
- Knowledge of vector databases such as:
1. Pinecone, Weaviate, FAISS, Chroma, pgvector
- Experience in deployment using:
1. Cloud Run / GKE / similar cloud services
- Exposure to evaluation frameworks such as:
1. RAGAS, Evals, custom evaluation pipelines
Agent Frameworks :
- Experience with any of the following :
1. LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen
Good to Have (Trainable) :
- Google Agent Development Kit (ADK)
- Gemini Enterprise / Agent Engine
- Model monitoring & observability tools
- Multi-agent system architecture
- Human-in-the-loop workflows
- Knowledge graph or enterprise search integration
Candidate Profile :
- Strong problem-solving and analytical mindset
- Ability to build end-to-end AI solutions from prototype to production
- Experience working in agile environments
- Excellent communication and collaboration skills
Skills
Machine Learning, Python, Generative AI, LangChain, Cloud Computing, Artificial Intelligence, MLOps, LLM, Data Science, Data Scientist