AI Applied Engineering Technical Leader

We are seeking a highly experienced AI Applied Engineering Technical Leader to shape the long-term AI architecture and engineering direction for a large enterprise healthcare organization.

Responsibilities:

• Define and drive the long-term technical strategy, reference architecture, and technology roadmap for AI-enabled products and platforms.
• Establish architectural patterns and best practices for retrieval systems, LLM orchestration, agentic workflows, human-in-the-loop processes, evaluation frameworks, and AI governance.
• Lead organization-wide technical decision-making regarding model strategy, vendor selection, platform investments, build-versus-buy decisions, and shared infrastructure capabilities.
• Design and champion scalable architectures that balance reliability, performance, security, compliance, maintainability, and cost efficiency.
• Establish engineering standards for evaluation, observability, model lifecycle management, responsible AI practices, and operational excellence.
• Build prototypes, proofs of concept, and reference implementations that de-risk emerging technologies and strategic platform investments.
• Lead cross-functional architecture reviews and provide technical guidance across multiple engineering teams.
• Mentor Lead Engineers, Senior Engineers, and emerging technical leaders through architecture reviews, design feedback, coaching, and technical sponsorship.
• Develop and communicate technical roadmaps aligned with business strategy and organizational objectives.
• Partner with executive leadership to translate business priorities into technical strategies and communicate technical opportunities, risks, and tradeoffs.
• Represent engineering in strategic vendor evaluations, compliance discussions, governance reviews, and enterprise planning initiatives.
• Drive adoption of common platforms, standards, and engineering practices across teams.
• Ensure AI systems are designed and operated in accordance with privacy, security, compliance, governance, and auditability requirements.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 12+ years of software engineering experience, including extensive experience designing and operating large-scale distributed systems.
• Proven track record of designing, delivering, and operating production AI-enabled platforms or products at enterprise scale.
• Deep expertise in large language model technologies, AI platform design, retrieval-augmented generation (RAG), agentic systems, orchestration frameworks, evaluation methodologies, and AI operations.
• Extensive experience designing cloud-native architectures and highly scalable, resilient systems.
• Demonstrated ability to define technical direction that influenced teams, organizations, or product portfolios beyond direct reporting relationships.
• Experience establishing engineering standards, architectural frameworks, or technical platforms that have been successfully adopted across multiple teams.
• Strong understanding of AI operational challenges, including model reliability, latency, cost optimization, governance, observability, and risk management.
• Demonstrated success influencing executive stakeholders and driving organizational decisions through technical leadership and evidence-based recommendations.
• Expert-level proficiency in Python and/or TypeScript/JavaScript.
• Ability to prototype, debug, review, and contribute code across multiple layers of the technology stack.

Preferred Qualifications:

• Experience leading AI platform strategy across multiple business units or product organizations.
• Experience developing enterprise standards for AI evaluation, testing, observability, governance, and responsible AI practices.
• Expertise evaluating and managing AI vendor ecosystems across multiple model providers and platform technologies.
• Experience building shared AI infrastructure and platform capabilities consumed by multiple engineering teams.
• Experience with agentic architectures, Model Context Protocol (MCP), workflow orchestration, autonomous systems, and emerging AI frameworks.
• Experience operating AI systems at significant scale while managing performance, reliability, and cost tradeoffs.
• Experience working in regulated industries such as healthcare, financial services, life sciences, or government.
• Deep understanding of privacy, security, compliance, governance, and risk management requirements in highly regulated environments.
• Experience driving adoption of AI-assisted software development practices across engineering organizations.
• Experience advising executive leadership on emerging technologies, platform strategy, and enterprise architecture decisions.
• Exceptional communication, leadership, collaboration, and strategic problem-solving skills.

Benefits:

• Medical, dental, and vision benefits
• 401(k) retirement savings plan
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
• Short-term and long-term disability
• Life insurance

Work Schedule:

• Hybrid work schedule, requiring employees to work three days per week in the office and the remaining days remotely.

Salary Range:

• $206,600 - $284,300 per year