- Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.
- Lead by example in using reactive firefighting to drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
- Design and implement resilient cloud ML/AI operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability).
- Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our ML/AI systems, workloads and processes.
- Design and implement both workflow automation, and more advanced agentic systems, across the organization using AWS GenAIServices and bleeding edge agentic stacks and frameworks
- Ensure principled and methodical validation pathways and a Well Architected Framework for Embryonic Research (WAFER) similar to and building on AWS’s Well Architected Framework (WAF) for all early stage GenAI PoC’s across the organization.
- Maintain and teach advanced understanding of rapidly evolving frameworks such as DSPy, Letta (formerly MemGPT), LlamaIndex, LangChain, and RAG to enhance AI capabilities across engineering and science organizations.
- Apply advanced prompt engineering techniques to improve AI model interactions and outputs, and evangelize “prompts as programs” philosophy and management/governance implications.
- Embed deeply within and across product, design, science and business teams to identify, scope and integrate workflow automation and agentic systems that have tangible and quantifiable product and business impact.
- Customer-obsessed and passionate about building products that solve real-world problems.
- Highly organized and detail-oriented, with the ability to manage multiple initiatives and deadlines.
- Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive.
- Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture.
- Expertise in RAG methodology and AWS Bedrock, Sagemaker, Lex and OpenSearch for developing AI and automation solutions.
- Expertise in the latest GenAI frameworks and tools like DSPy, Letta, LlamaIndex, and LangChain.
- Advanced coding skills in relevant programming languages (Python/JavaScript/TypeScript) and frameworks.
- Similar cloud operations skills as an ML/AI Platform Architect, with an emphasis on workflow automation.
- Minimum of 7 years in workflow automation and 2 years at the forefront of the emergence of agentic systems.
- Proven track record of leading complex projects involving ML/AI and automation technologies.
- Demonstrated ability to identify real business and product opportunities and implementing cutting-edge technologies and methodologies in production environments to drive tangible and quantifiable product and business value.
- Experience working with diverse teams to achieve product and organizational objectives through automation.
- HS Diploma and 8 years of experience in Engineering/IT solutions OR BA/BS Degree and 5 years of experience or equivalent capabilities.
- Preferred Education: M.S. or PhD in Computer Science or related field.
- Qualified retirement program [401(k) plan]
- Paid vacation and holidays
- Paid leaves
- Health benefits including medical, prescription drug, dental, and vision coverage