Note: The job is a remote job and is open to candidates in USA. Insight Global is seeking a hands-on AI Engineer to join its Innovation team and explore emerging generative AI patterns, graph-driven architectures, and agentic workflows. The role focuses on rapidly prototyping and demonstrating AI proofs of concept, building end-to-end pipelines, evaluating tools, and documenting findings for production handoff.

Responsibilities

• Design and ship rapid PoCs across GenAI use cases: RAG, agentic workflows, LLM orchestration, semantic search, and knowledge graphs
• Apply graph theory and graph-based data structures (Neo4j, NetworkX, GraphRAG, LangGraph) to model relationships, enable multi-hop reasoning, and power retrieval systems
• Build end-to-end AI pipelines integrating LLMs (OpenAI, Anthropic, Azure OpenAI, Hugging Face) with vector stores, embeddings, and enterprise data
• Write clean, performant SQL to shape training/eval datasets and integrate structured data into GenAI workflows
• Evaluate emerging tools and frameworks (LangChain, LangGraph, LlamaIndex, MCP, Pinecone, Weaviate, FAISS) and recommend what earns a spot in the stack
• Partner with product, data science, and business stakeholders to translate ambiguous problems into demoable prototypes within tight sprints
• Document findings, benchmarks, and trade-offs so successful PoCs can hand off cleanly to production teams

Skills

• 3+ years of engineering experience with at least 1+ years hands-on in AI/ML or GenAI
• Strong Python
• Production comfort with LangChain, LangGraph, or equivalent LLM orchestration frameworks
• Demonstrated experience with Generative AI: RAG, prompt engineering, embeddings, fine-tuning (LoRA/PEFT), agentic systems
• Working knowledge of graph theory — graph databases, graph algorithms, or GraphRAG-style retrieval
• Solid SQL and comfort working with structured + unstructured data
• GCP Cloud experience, including GKE, Big Query, Vertex AI, etc

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