Define and communicate the long-term vision for Generative AI and platform capabilities
Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively
Lead the enterprise-level architectural design and technical strategy for major components of our generative AI applications and platform
Partner with senior engineering managers, product leaders, and data scientists / MLEs to translate strategic objectives into executable architectural blueprints
Drive the adoption of superior engineering standards and advanced AI evaluation frameworks like LangSmith
Spearhead technical solutioning for the platform's most complex challenges
Mentor and cultivate a team of associate architects and senior engineers
Own and execute a significant portion of the technology roadmap
Oversee design and deployment of enterprise-scale GenAI platforms, inference pipelines, and AI-powered applications
Ensure operational excellence in LLM Ops, including automation, observability, and lifecycle management
Champion adoption of cutting-edge generative AI techniques
Requirements
PhD in Computer Science, AI, or related field with 10+ years in AI/ML engineering (preferred); or MS with 12+ years of experience
Minimum 5 years in senior leadership roles managing managers and large engineering teams
Proven track record in building enterprise level production-grade GenAI platforms and services and strong problem-solving skills
In-depth knowledge and hands-on experience with LLM fine-tuning, model optimization, context graphs, automation, and advanced prompting strategies
Deep knowledge of LLM lifecycle tools, distributed systems, and cloud-native architectures
Architect and implement enterprise-grade LLM-powered solutions, managing the full lifecycle from business requirements to production deployment, monitoring, and continuous optimization
Design and develop multi-agent GenAI systems using state-of-the-art frameworks (LangChain, LlamaIndex) to orchestrate complex workflows across retrieval augmentation, data operations, and compliance verification
Engineer robust Retrieval Augmented Generation (RAG) pipelines incorporating advanced techniques such as hybrid retrieval, reranking, query expansion, and contextual compression
Implement parameter-efficient fine-tuning strategies (LoRA, QLoRA, PEFT) to adapt foundation models to domain-specific use cases while optimizing for inference costs and latency
Develop intelligent routing and orchestration systems to manage conversation state across multiple specialized AI agents, ensuring seamless transitions between different system capabilities
Build evaluation frameworks to measure and improve LLM performance across diverse metrics, including factuality, coherence, task completion, and alignment with business objectives
Integrate LLM solutions with existing enterprise architecture, ensuring compliance with data security policies, authentication mechanisms, and transaction safety requirements
Tech Stack
Cloud
Distributed Systems
Benefits
Excellent benefits package that includes 401(K) match
Adoption assistance
Parental leave
Tuition reimbursement
Comprehensive medical/ dental/vision
Many nonstandard benefits that make us a Great Place to Work