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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