• Define and drive the multi-year technical roadmap for the Core GenAI Platform, influencing adoption and alignment across several engineering teams • Collaborate with CTO/VP-level and above leadership to influence business strategy with technical insight • Lead architecture and design of large-scale, mission-critical systems for model inference, orchestration, and compliance • Identify and solve systemic technical risks that impact the entire company and business-critical AI initiatives • Represent Upstart internally and externally as a thought leader in GenAI systems through executive reviews, cross-company forums, and industry venues • Establish operational standards for GenAI integrations, ensuring security, fairness, and reliability at scale • Build high-leverage, generalizable platform components that meaningfully accelerate the productivity of engineers across Upstart • Mentor senior engineers, other principal engineers, and shape the growth of future technical leaders, fostering a culture of learning and excellence

• Develop and implement AI solutions using frameworks such as LangChain, LangGraph, and multi-agent systems. • Utilize prompt engineering and retrieval-augmented generation (RAG) to enhance AI capabilities. • Work with vector databases (ChromaDB, Pinecone) and implement context optimization and model routing. • Ensure LLM observability and adherence to AI governance standards. • Lead Agile teams through project lifecycles from conception to deployment, ensuring best practices in software development and architecture. • Manage CI/CD processes, including logging, tracing, and monitoring for infrastructure observability. • Conduct code reviews and enforce design patterns to maintain high-quality code standards. • Collaborate effectively with stakeholders to align on project goals and deliverables.

• Develop and implement AI solutions using frameworks such as LangChain, LangGraph, and multi-agent systems. • Utilize prompt engineering and retrieval-augmented generation (RAG) to enhance AI capabilities. • Work with vector databases (ChromaDB, Pinecone) and implement context optimization and model routing. • Ensure LLM observability and adherence to AI governance standards. • Lead Agile teams through project lifecycles from conception to deployment, ensuring best practices in software development and architecture. • Manage CI/CD processes, including logging, tracing, and monitoring for infrastructure observability. • Conduct code reviews and enforce design patterns to maintain high-quality code standards. • Collaborate effectively with stakeholders to align on project goals and deliverables.

• Translate high-level business problems into functional AI solutions by creating and executing end-to-end solutions • Design, build, and maintain backend services and APIs that deploy and integrate AI-powered features using existing foundational models (e.g., OpenAI, Claude, Hugging Face, etc.) • Implement scalable, reliable, and maintainable backend architecture supporting AI workflows, automation, and data processing pipelines • Integrate AI services into complex technology stacks, ensuring interoperability with microservices, AWS platform, and data systems (Snowflake) • Enable rapid test-and-learn cycles by building experimentation frameworks that support iterative deployment of AI-driven functionalities • Collaborate closely with cross-functional teams including product managers, data scientists, and frontend engineers to translate business needs into technical implementations • Stay abreast of the AI ecosystem, frameworks, and tools to guide implementation decisions and technical evaluations for adopting new AI capabilities • Document backend system designs, APIs, workflows, and integration patterns clearly for team knowledge sharing and operational continuity.