AI/ML Tech Lead

We are looking for an AI/ML Tech Lead to lead the design and development of production-grade AI solutions for real-world business challenges. This is a hands-on leadership role where you'll define technical architecture, make key engineering decisions, mentor developers, and build scalable AI systems powered by LLMs, RAG, and agentic workflows.

Part-time during the first month, with the opportunity to transition into a long-term collaboration.

Required Skills & Experience

• 6+ years of commercial software development experience (strong Python experience preferred)
• 2+ years leading AI/ML projects or technical teams
• Proven experience designing and delivering production AI/LLM applications
• Strong understanding of modern AI/ML architectures, LLM ecosystems, and agent-based systems
• Hands-on experience with TensorFlow, PyTorch, or similar ML frameworks
• Experience with LLM APIs (OpenAI, Claude, Gemini, etc.)
• Deep understanding of RAG pipelines, vector databases, embeddings, and retrieval strategies
• Experience designing scalable APIs and integrating third-party services
• Strong software architecture and system design skills
• Excellent communication and technical leadership skills
• Comfortable working in fast-paced startup environments

Nice to Have

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar frameworks
• Experience with model fine-tuning (LoRA, QLoRA, adapters)
• Knowledge of AWS/GCP/Azure AI services
• Experience leading distributed engineering teams
• Experience working directly with enterprise clients
• Background in AI Engineering, Machine Learning, or Data Science

Responsibilities

• Lead the architecture and implementation of AI-powered products and services
• Design scalable agentic systems and multi-agent workflows
• Define and optimize RAG pipelines and retrieval strategies
• Guide model selection, evaluation, fine-tuning, and prompt engineering best practices
• Review code, mentor engineers, and establish engineering standards
• Drive technical decisions and ensure solution scalability, reliability, and maintainability
• Collaborate with product managers, clients, and stakeholders to translate business needs into technical solutions
• Support delivery of production-ready AI systems and continuously improve development processes