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
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