Staff Forward Deployed Engineer

About Judi Health Judi Health is a health technology company providing benefit administration solutions to employers, unions, health plans, and government entities. Judi Health replaces fragmented, outdated systems with the industry's first Unified Claims Processing™ architecture, seamlessly consolidating pharmacy and medical benefit administration on a single, secure platform. By delivering true price transparency, eliminating unnecessary middleman fees, and leveraging advanced AI-powered care delivery, Judi Health helps clients achieve unprecedented operational efficiency and service levels. At Judi Health, we're deploying the infrastructure our country needs to deliver the healthcare we all deserve. We are the intelligence platform powering benefits plans for millions of Americans and proudly leading the next generation of care. To learn more, visit www.judi.health . Location: New York City, NY (hybrid) Position Summary The Staff Forward Deployed Engineer is a senior individual contributor who leads the company's most complex, high-impact AI use cases from discovery through implementation. Working with a high degree of autonomy, the role partners with senior business and technology leaders to translate ambiguous, cross-functional problems into scalable AI solutions with measurable business outcomes. The Senior FDE designs and builds solutions using AI agents, large language models, and agentic coding tools; sets technical direction for solution design and readiness; and establishes reusable patterns that can scale across the enterprise or contribute to future client-facing products. The role provides technical leadership and mentorship to interns, analysts, and associate forward deployed engineers without formal people-management responsibility. Position Responsibilities: • Lead Complex AI Use Cases: Lead the most complex and high-impact AI initiatives, particularly those spanning multiple functions, workflows, systems, or data sources; determine the solution approach, scope, priorities, and sequencing, and own outcomes from discovery through implementation. • Senior Stakeholder Partnership: Serve as a trusted advisor to senior business and technology leaders, structure ambiguous business challenges, evaluate trade-offs, and recommend scalable solutions tied to measurable outcomes and long-term enterprise value. • Agentic Solution Design and Development: Architect and build AI solutions using AI agents, LLMs, retrieval-augmented generation, orchestration frameworks, and agentic coding tools; select appropriate technologies and critically evaluate AI-generated outputs. • Technical Direction and Production Readiness: Set technical direction for solution design and partner closely with the AI Deployment Engineer and relevant technology teams to meet production-readiness requirements, including performance, scalability, observability, security, compliance, supportability, and operational ownership. • Reusable Patterns and Enterprise Value: Establish reusable solution patterns, frameworks, components, and practices that accelerate future delivery; identify opportunities for internal capabilities to scale across the company or contribute to future client-facing products. • Value Realization: Define success measures, assess adoption and business impact, and recommend enhancements or course corrections to maximize the long-term value of deployed solutions. • Risk and Governance: Identify and mitigate technical, data privacy, security, compliance, and responsible AI risks, ensuring solutions align with enterprise standards and applicable regulatory requirements. • Mentorship and Team Standards: Mentor interns, analysts, and associate forward deployed engineers through design reviews, code reviews, and hands-on guidance; raise team standards and lead workstreams without formal people-management responsibility. • Technology Evaluation and Continuous Improvement: Evaluate emerging AI technologies, agentic frameworks, and delivery practices, and use findings to improve the team's technical standards, shared toolkit, and delivery approach. Required Qualifications: Education and Experience • Bachelor's degree in Engineering, Computer Science, Information Technology, Data Science, or another technically rigorous discipline required; an equivalent combination of education and relevant experience may be considered. • 5-8 years of progressive experience across technology consulting, solutions engineering, applied AI, automation, product development, business technology, or software engineering. • Demonstrated experience leading complex, cross-functional technical initiatives from problem definition through implementation and production readiness. • Advanced hands-on experience building solutions with LLMs, AI agents, retrieval-augmented generation, agentic frameworks, automation, or API-based integrations. • Experience partnering directly with senior business and technology stakeholders in an internal consulting, client-facing, or business technology capacity. • Experience in healthcare, pharmacy benefit management, or another regulated industry is preferred, but not required. Knowledge, Skills and Abilities • Advanced knowledge of generative AI and applied AI concepts, including large language models, prompt design, retrieval-augmented generation, AI agents, orchestration, and solution evaluation. • Advanced hands-on capability in one or more programming or scripting languages, such as Python, TypeScript, or Java, together with agentic coding tools, APIs, cloud platforms, and modern development practices. • Strong knowledge of systems integration, enterprise solution design, and production-readiness considerations, including security, observability, scalability, maintainability, and supportability. • Working knowledge of responsible AI, data privacy, information security, compliance, and regulatory requirements applicable to enterprise AI solutions. • Ability to translate am