Senior AI Lead

• AI Practice Leadership: Act as a senior technical authority to help define and scale our AI engineering practices. Create reference architectures, development blueprints, and best-practice guidelines for building advanced AI solutions
• Hands-On Prototyping & Framework Development: Lead the design and development of core AI frameworks and libraries. Build production-quality proof-of-concepts and reference implementations for complex patterns like advanced RAG pipelines and multi-agent systems
• AI Evaluation at Scale: Architect and implement a comprehensive, enterprise-grade AI evaluation framework. This includes defining key metrics, developing automated testing pipelines, and establishing processes to continuously evaluate the performance, accuracy, safety, and cost of our AI models and systems
• Technical Mentorship & Evangelism: Serve as a senior mentor to AI engineers across the organization. Evangelize best practices in AI engineering, MLOps, and system evaluation through workshops, documentation, and direct consultation
• Expert Consultation: Act as the go-to expert for application teams on advanced AI topics. Provide deep technical guidance on architecture, tool selection, and implementation challenges related to RAG, agentic systems, and large-scale deployment
• Practical Problem Solving: Partner with business and technology teams to tackle the most challenging problems. Apply your deep expertise to architect and deliver practical, efficient, and scalable AI solutions that create tangible business value

• 12+ years of experience in software engineering, with at least 5-7 years in a senior, hands-on AI/ML engineering role
• Deep, hands-on experience building and deploying sophisticated, large-scale AI systems
• Proven, practical expertise in modern AI techniques, specifically designing, building, and optimizing Retrieval-Augmented Generation (RAG) pipelines
• Demonstrable experience in architecting and developing agentic AI ecosystems (e.g., using frameworks like LangChain, LlamaIndex, Autogen, or custom-built agentic frameworks)
• Expert-level knowledge of AI evaluation methodologies and frameworks
• Must have practical experience designing and implementing automated evaluation pipelines at scale to test for quality, toxicity, hallucination, and accuracy
• Expert-level programming skills, particularly in Python, and deep familiarity with major AI/ML libraries (e.g., PyTorch, Hugging Face, LangChain, LlamaIndex, Scikit-learn)
• Strong experience with LLM Operations (LLMOps/MLOps), including model deployment, monitoring, fine-tuning, and lifecycle management
• Solid experience with cloud platforms (AWS, Azure, GCP) and their associated AI/ML services
• A true practitioner with a passion for staying hands-on and writing code
• A pragmatic and practical problem-solver who can navigate complex technical challenges and deliver effective, real-world solutions
• Proven ability to mentor senior engineers and provide technical leadership across a large organization
• Excellent communication skills with the ability to articulate highly complex technical concepts to both technical and non-technical audiences
• Bachelor’s degree in Computer Science, Engineering, or a related quantitative field
• Master’s or PhD in Computer Science, AI, or a related field is strongly preferred (nice to have)

Master’s or PhD in Computer Science, AI, or a related field is strongly preferred