Lead AI Applied Engineer

We are seeking a Lead AI Applied Engineer to provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems.

Responsibilities:

• Own the architecture, design, and evolution of full-stack AI applications, including LLM pipelines, retrieval systems, agentic workflows, human-in-the-loop processes, and supporting platform services.
• Design and implement scalable AI solutions that prioritize reliability, accuracy, auditability, performance, and cost efficiency.
• Build and maintain the most complex and high-risk system components where architecture and implementation decisions have significant business impact.
• Define and enforce engineering standards for AI systems, including evaluation methodologies, structured outputs, observability, testing, fallback strategies, latency optimization, and cost controls.
• Lead technical design reviews and guide architecture decisions related to platform capabilities, AI systems, integrations, infrastructure, and software patterns.
• Evaluate and recommend technologies, frameworks, AI models, and third-party solutions based on technical and business requirements.
• Translate ambiguous business goals into clear technical strategies, roadmaps, and executable workstreams.
• Provide technical leadership across multiple projects, ensuring alignment with architectural standards and long-term platform objectives.
• Mentor and coach engineers through design reviews, code reviews, pair programming, and technical guidance.
• Partner with product, engineering, clinical, and operational stakeholders to deliver solutions that meet business and regulatory requirements.
• Own operational excellence, including deployment strategies, monitoring, incident management, and production reliability.
• Ensure all solutions comply with privacy, security, governance, and audit requirements within a regulated healthcare environment.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of software engineering experience, including experience designing and operating production systems at scale.
• Proven track record of delivering AI-enabled products or platforms into production environments.
• Deep hands-on experience integrating and operating LLMs within business-critical workflows.
• Experience designing systems that leverage structured outputs, tool calls, retrieval-augmented generation (RAG), agentic workflows, orchestration frameworks, and evaluation pipelines.
• Experience making architectural decisions for systems where AI is a core component of the product experience.
• Demonstrated success leading technical initiatives across engineering teams, including architecture reviews, technical planning, mentoring, and delivery execution.
• Strong programming skills in Python and/or TypeScript/JavaScript.
• Experience designing and operating distributed systems, APIs, data platforms, and cloud-native applications.
• Strong understanding of reliability engineering, system performance, scalability, and operational excellence.
• Ability to balance technical tradeoffs involving quality, latency, cost, security, and maintainability.

Preferred Qualifications:

• Experience taking AI products from concept through production deployment and long-term operational ownership.
• Experience developing AI systems where LLMs are part of critical decision-support or operational workflows.
• Expertise in evaluation frameworks, benchmark datasets, regression testing, model quality measurement, and human review processes.
• Experience with agentic systems, Model Context Protocol (MCP), workflow orchestration, multi-step reasoning frameworks, and AI observability platforms.
• Experience with React, Next.js, modern frontend technologies, and full-stack application development.
• Experience deploying and managing workloads using Kubernetes, Docker, modern CI/CD platforms, and cloud-native technologies.
• Experience with Google Cloud Platform, Azure, AWS, Vertex AI, or comparable AI and cloud infrastructure platforms.
• Experience working in highly regulated industries such as healthcare, financial services, or government.
• Knowledge of privacy, compliance, security, and governance frameworks impacting AI and data-driven applications.
• Experience implementing AI-assisted development practices that improve engineering productivity and delivery speed.
• Excellent communication, collaboration, problem-solving, and leadership 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 (3 days in office, 2 days remote) Scheduled Weekly Hours: 40 Pay Range: $170,800 - $234,800 per year