Senior AI / LLM Lead (Contract) — High Priority Role

Location:

Experience:

Contract:

Senior AI / LLM Lead

What You’ll Do

LLM Architecture & Optimization

• Design enterprise-ready

  LLM-based reasoning frameworks

• Architect

  RAG pipelines

  combining structured & unstructured enterprise knowledge
• Fine-tune and optimize

  foundation models

  for diagnostics, troubleshooting & decision support
• Build scalable

  prompt orchestration frameworks

  (hierarchical, adaptive, tool-use prompts)
• Evaluate emerging

  LLM modalities

  — multimodal, reasoning-augmented, and tool-enabled models

Knowledge Engineering

• Partner with SMEs to extract and embed expert knowledge
• Develop

  semantic embeddings

  , vector stores, and hybrid retrieval systems
• Build & maintain

  domain ontologies

  , entity graphs, and factual grounding systems
• Ensure model transparency using

  citation generation

  & provenance tracking

Agentic AI & Multi-Model Integration

• Integrate LLMs into

  multi-agent architectures

• Define LLM–tool interaction schemas with Agentic AI teams
• Build adaptive memory using

  vector, relational & graph storage

Performance, Safety & Evaluation

• Create evaluation pipelines for accuracy, grounding, coherence & bias
• Implement

  RLHF

  and continuous learning feedback loops
• Run A/B tests on prompts, architectures & retrieval strategies
• Ensure compliance with

  AI governance, privacy & ethical standards

What You Bring

• Deep expertise in

  transformer architectures

  , fine-tuning & LLM optimization
• Strong experience with

  RAG systems

  , embedding models & retrieval frameworks
• Proficiency in

  Python, PyTorch

  , and distributed inference optimization
• Hands-on experience with

  multi-agent orchestration

  (AutoGen, Semantic Kernel, LangChain Agents)
• Strong understanding of prompt engineering, context management & token efficiency
• Experience building

  knowledge graphs

  , vector databases & retrieval APIs
• Strong analytical skills for LLM evaluation & experiment design

Preferred Qualifications

• 7+ years in applied NLP, ML, or AI systems
• 2+ years working directly with LLM fine-tuning or enterprise RAG systems
• Graduate degree in CS, ML, Computational Linguistics or related fields
• Experience in industrial, engineering, or diagnostics domains (plus)