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We are seeking a Hands-On GenAI Lead to provide technical authority and hands-on leadership for the architecture, design, delivery, and evolution of enterprise-scale generative AI platforms and solutions. This role represents the highest individual contributor level, combining deep technical execution with strategic architectural ownership across multiple GenAI initiatives.

The GenAI Lead is a builder, architect, and technical leader who shapes GenAI strategy through implementation, sets engineering standards, and solves the organization''s most complex GenAI challenges — while remaining actively involved in design reviews, coding, experimentation, and production deployments.

Key Responsibilities

GenAI Technical Authority & Architecture

• Act as the principal technical authority for GenAI and LLM-based systems across the organization.
• Define and evolve enterprise GenAI architectures, reference implementations, and design patterns.
• Own architectural decisions for multi-agent systems, orchestration frameworks, and complex workflows using CrewAI, LangGraph, or equivalent.
• Lead the design of large-scale complex document intelligence and parsing solutions, setting the bar for quality and performance.

Hands-On Engineering & Problem Solving

• Remain deeply hands-on, contributing to critical code paths, prototypes, and production systems.
• Design, build, fine-tune, evaluate, and deploy advanced LLM solutions (copilots, autonomous agents, RAG systems, summarization, extraction, chatbots).
• Solve the most complex GenAI challenges involving performance, scalability, latency, cost, and reliability.
• Drive advanced prompt engineering, evaluation frameworks, and fine-tuning strategies.

Platform & Production Excellence

• Lead the development of reusable GenAI platforms, frameworks, and shared services.
• Establish best practices for model lifecycle management, observability, evaluation, and governance.
• Ensure GenAI solutions meet enterprise requirements for security, compliance, robustness, and responsible AI.
• Partner with cloud, platform, and Governance teams to ensure production readiness at scale.

Technical Leadership Without Line Management

• Provide technical mentorship and guidance to Lead and Senior GenAI engineers.
• Set coding standards, review complex designs, and raise the overall technical bar.
• Influence technical direction across teams without direct people management responsibility.
• Act as a trusted advisor to engineering leadership, product leaders, and executives.

Innovation, Strategy & Thought Leadership

• Continuously evaluate emerging LLMs, orchestration frameworks, and GenAI tooling.
• Influence GenAI roadmap and investment decisions through technical insight and experimentation.
• Drive responsible AI practices, including bias mitigation, explainability, and risk management.
• Represent the organization internally and externally as a GenAI technical thought leader.

Required Skills & Technologies

Core Technical Expertise

• Programming: Python (expert-level), Java / TypeScript (for system integrations)
• GenAI Frameworks: Hugging Face Transformers, LangChain, OpenAI API, or equivalents
• LLMs: Deep hands-on experience with state-of-the-art models (GPT-4/5-class, Claude, Grok, or similar)
• Orchestration: CrewAI, LangGraph, or other multi-agent orchestration systems
• ML Frameworks: PyTorch, TensorFlow, or JAX
• Retrieval & Data: RAG pipelines, embeddings, vector databases, document chunking strategies
• Deployment: Docker, Kubernetes, FastAPI, CI/CD pipelines
• Cloud Platforms: Azure, AWS, or Google Cloud Platform

Qualifications

• Bachelor''s or Master''s degree in Computer Science, AI, Data Science, or related field.
• 8+ years of hands-on software, ML, or AI engineering experience.
• 4+ years delivering GenAI or LLM-based systems in production.
• Demonstrated experience owning architecture across multiple GenAI initiatives.
• Proven ability to influence technical direction at an organizational level.
• Strong communication skills with both deeply technical and executive audiences.

Preferred Qualifications

• Experience designing enterprise GenAI platforms or internal AI frameworks.
• Hands-on work with multi-agent or autonomous GenAI systems in production.
• Contributions to open-source GenAI projects, internal platforms, or technical publications.
• Experience operating in regulated or high-risk environments requiring strong AI governance