AI Engineer

Responsibilities:

• Build AI agents for resume analysis, candidate search, screening, technical assessments, and job matching.
• Develop workflows using LLMs, retrieval-augmented generation (RAG), tool calling, and Model Context Protocol (MCP).
• Adapt open-source models using supervised fine-tuning and techniques such as LoRA/QLoRA.
• Build data pipelines to clean, deduplicate, and prepare resumes, job descriptions, and assessment data.
• Create evaluations to measure accuracy, relevance, hallucinations, latency, and cost.
• Deploy and monitor production AI services, improving reliability and inference performance.
• Implement safeguards for candidate privacy, data security, and fair evaluation.
• Collaborate with engineering and product teams to turn experiments into working features.

Requirements:

• Strong Python programming and backend API development experience.
• Hands-on experience building and deploying LLM-powered applications.
• Working knowledge of embeddings, vector search, RAG, structured outputs, and tool calling.
• Experience with PyTorch, Hugging Face Transformers, or similar frameworks.
• Understanding of model evaluation, dataset quality, and fine-tuning fundamentals.
• Experience with SQL, Docker, Git, and cloud infrastructure.
• Ability to independently debug problems and deliver production features.