• Conduct research and development of novel AI/ML concepts, algorithms, and techniques to advance space and missile defense capabilities • Lead the design, development, and testing of scalable AI/ML software prototypes for space and missile defense using large-scale datasets • Interface with customers and stakeholders to gather mission requirements, present technical solutions, and ensure project alignment • Mentor and guide junior engineers, fostering a culture of technical excellence and collaboration • Track project milestones and budgets, ensuring timely and quality outcomes • Support proposal-writing activities and thought leadership opportunities • Engage in continuous learning and professional development to stay at the forefront of AI/ML advancements, space domain technologies, and relevant emerging R&D trends

• Lead the design, development, testing, and deployment of AI/ML software prototypes. • Own technical direction and architecture for assigned efforts and ensure consistency across projects. • Drive technical planning, estimation, and execution across customer-funded and internal R&D efforts, including defining and tracking technical milestones and deliverables. • Conduct design and code reviews to ensure quality, scalability, and maintainability. • Identify and manage technical risks related to data, models, system integration, and dependencies. • Serve as the primary technical interface with customers, presenting designs, results, and tradeoffs clearly. • Lead and mentor a team of engineers, supporting team growth, capability development, and scaling of engineering practices. • Improve team effectiveness through structured planning, clear prioritization, and timely resolution of technical and organizational blockers. • Ensure engineering efforts align with customer needs and company objectives. • Lead or contribute to proposal development, including shaping technical approaches, estimates, and solution strategies.

• Agentic System Design: Design, build, and maintain production-grade agentic systems, multi-agent orchestration, specialist agents, and Human-in-the-Loop workflows, with context management, memory, and tool-calling. • MCP & Tool Integration: Develop MCP servers and tool integrations connecting AI agents to Teak's platform APIs and partner systems. • LLM Integration & Output Control: Orchestrate LLMs (Claude, GPT, Gemini, or similar) across the AI layer, selecting the right model per task and managing prompt and system-prompt strategies so agents present refund solutions in pre-approved, compliant language. • RAG & Knowledge Systems: Build RAG pipelines that ground agent responses in Teak's policy and product data, with versioning and isolation that prevent hallucination on compliance-sensitive topics. • Compliance & Safety: Implement guardrails that enforce compliant offer language, prevent unauthorized coverage claims, and meet regulatory requirements across Teak's markets. • Evaluation: Build evaluation frameworks to monitor, test, and continuously improve agent performance, reliability, and output quality. • AI Infrastructure & Observability: Build and operate AI infrastructure on AWS, with structured logging and tracing for auditability and rapid issue resolution. • Backend Development: Contribute to backend services, APIs, and platform improvements in Python alongside AI work, applying clean code, testing, and strong engineering fundamentals. • Collaboration & Code Quality: Participate in code reviews, document agent system design and integration patterns, take part in Agile workflows, and join the on-call rotation.

Role Description This is a high-impact technical leadership role within the Optum Tech AI Transformation team, supporting key enterprise initiatives such as the Real-Time AI Underwriting platform. You will own the technical direction and people leadership for a squad of AI/ML engineers, driving strategic engineering efforts. Beyond building, you will lead, mentor, govern, and ensure that everything your team delivers meets the highest standards of quality, compliance, and Responsible AI. You'll serve as a bridge between engineering execution and leadership vision, ensuring AI investments translate into measurable, production-grade business outcomes. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. - Design, develop, and deploy production-grade AI-powered solutions—spanning classical ML, Generative AI (LLMs, RAG, Graph RAG), and multi-agent orchestration frameworks—to address complex business challenges with emphasis on responsible and secure AI practices. - Own the end-to-end AI/ML technical roadmap, defining architectural direction, choosing optimal technologies, and establishing engineering and coding standards for the team's portfolio. - Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across the development lifecycle, optimizing team productivity and operational efficiency. - Evaluate emerging trends and technologies (such as Agentic AI, foundation models, fine-tuning, and enterprise AI tooling) to inform high-quality solution design and strategic innovation. - Drive MLOps maturity across development pipelines, overseeing model versioning, CI/CD for ML, retraining automation, drift detection, and production monitoring. - Ensure compliance and ethical governance by aligning solutions with enterprise policies, Responsible AI principles, and data privacy regulations (HIPAA/PHI handling). - Lead, mentor, and develop a team of 5–10 direct/indirect AI/ML engineers, setting clear goals, conducting regular 1:1s, and fostering a high-performance, self-managed culture. - Own and conduct robust technical reviews (architecture, design, and code reviews) to enforce rigorous standards, security posture, and pythonic best practices. Qualifications - 10+ years of software development experience with a strong engineering and architecture foundation. - 2+ years of hands-on experience in AI/ML project implementation (full lifecycle from ideation, data analysis, model development through production deployment). - Hands-on experience with NLP (text processing, embeddings, transformers, NER, text classification, or conversational AI). - Working experience with GenAI (RAG pipelines, prompt engineering, LLM integration, fine-tuning techniques like LoRA, and enterprise deployment). - Experience or strong working knowledge of Agentic AI development (agentic workflows, tool orchestration, multi-agent systems, or planning frameworks). - Solid Python programming skills with deep proficiency in production-grade coding, code reviews, and enforcing standards. - Driver’s License and access to a reliable transportation. Preferred Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent professional experience). - Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, etc.) for experiment tracking, model registry, and automation. - Familiarity with Responsible AI frameworks (bias detection, fairness metrics, model explainability like SHAP/LIME, and adversarial red-teaming). - Knowledge of Graph RAG, knowledge graphs, and ontology-based reasoning systems. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements). Application Deadline This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.