Required Skills : * Local-First AI Expertise: Proven track record deploying and optimizing open-source LLMs (e.g., LLaMA, Mistral) in non-cloud, restricted, or air-gapped private infrastructures * Deep Framework Proficiency: Heavy hands-on experience with PyTorch, Hugging Face, and orchestration layers like LangChain, LlamaIndex, or equivalent frameworks * Vector and Retrieval Mastery: Direct experience engineering production-grade RAG architectures, embeddings, semantic search, and local vector databases (e.g., FAISS, Qdrant, Milvus, Chroma) * Containerization and Compute Infrastructure: Strong experience containerizing AI workloads via Docker/Kubernetes and managing dedicated GPU-based compute environments * Advanced ML Concepts: Solid understanding of fine-tuning techniques (LoRA/QLoRA) versus prompt engineering, and model quantization formats (GGUF, AWQ, EXL2) * Autonomy: Ability to build, test, and iterate rapidly in an isolated development sandbox with zero dependency on third-party cloud APIs * Experience operating within heavily regulated or compliance-driven industries (e.g., high-governance data environments, fintech, or legal-tech) * Familiarity with local-first agentic workflows, Model Context Protocol (MCP), or building fully internal developer copilots and autonomous knowledge systems.
| 6 Month. Job Posting Title: Lead Full Stack Software Engineer - AI Assisted Engineering Practices Req ID: 10146000 Job Description: . The ideal candidate will have strong experience building scalable data pipelines, integrating data platforms, and supporting analytics solutions within a Databricks and Power BI ecosystem. Duration: July 6, 2026 January 25, 2027 Open Positions: 1 Position Overview Our client is seeking a highly motivated Data Engineer to join a newly established Data Center of Excellence (COE) and help shape the future of enterprise data and analytics capabilities. |