Head of AI Engineering

Accountabilities:
The Head of AI Engineering will own the architecture, execution, and evolution of AI platforms while ensuring reliability, safety, and scalability across production systems. Build and lead the development of an internal AI Agent SDK that enables engineers to create powerful, reliable, and reusable AI applications. Define AI architecture strategy, including agent frameworks, orchestration, context management, retrieval systems, memory, tooling, workflows, and runtime infrastructure. Serve as the technical owner for production AI systems, ensuring continuous improvement in quality, reliability, performance, and cost efficiency. Develop evaluation frameworks using automated checks, simulations, human feedback, and production outcomes to measure and improve AI system performance. Establish safe AI operating practices through authorization controls, validation processes, auditability, recovery mechanisms, and appropriate human escalation paths. Own model strategy, including model selection, routing, optimization, experimentation, fine-tuning approaches, and deployment decisions based on measurable outcomes. Build production observability, monitoring, testing, and incident response capabilities for AI-powered systems. Partner closely with engineering, product, and domain experts to translate complex business challenges into scalable AI solutions. Provide technical leadership, mentor engineers, establish engineering standards, and grow a high-performing applied AI team. Remain hands-on by contributing production code and personally building foundational AI capabilities while guiding broader technical direction. Develop strong relationships with external technology providers and represent the organization within the AI engineering community. Requirements: The ideal candidate is an experienced AI engineering leader with strong software engineering fundamentals, a proven ability to ship production AI systems, and the technical judgment required to operate in complex environments. 8+ years of software engineering experience with continued involvement in production development. Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical discipline. Demonstrated experience building and launching production-grade AI agents capable of reasoning, using tools, managing state, and operating under real-world constraints. Deep understanding of AI agent architectures, including orchestration, retrieval, memory, context construction, workflows, and error recovery. Experience designing evaluation systems for AI products, including benchmarking, simulations, regression detection, and production performance measurement. Strong systems engineering background with expertise in APIs, distributed systems, databases, observability, reliability, and scalable infrastructure. Ability to design AI systems that support safe and controlled execution of consequential actions. Strong understanding of modern AI models, including their capabilities, limitations, optimization approaches, and appropriate use cases. Experience leading engineering teams, setting technical direction, mentoring developers, and maintaining high execution standards. Ability to communicate complex technical concepts clearly to engineers, executives, product teams, and non-technical stakeholders. Proven ability to operate independently, make strategic decisions, and create clarity in fast-moving environments. Strong ownership mindset with the ability to take responsibility for outcomes, reliability, and continuous improvement. Preferred qualifications include: Experience building AI platforms, agent runtimes, SDKs, evaluation systems, or shared AI infrastructure. Experience developing customer-facing AI agents, transactional systems, or high-volume automation platforms. Background working with healthcare, finance, insurance, or other high-impact industries requiring reliability and compliance. Experience fine-tuning, evaluating, or deploying open-weight AI models in production. Experience with long-term memory systems, personalization, real-time AI applications, or streaming architectures. Experience collaborating directly with AI model providers on technical integrations, evaluations, and performance optimization. Strong ability to identify and recruit exceptional AI engineering talent. Benefits: Competitive compensation package ranging from $200,000 to $400,000 annually , plus equity opportunities. Fully remote work environment with flexibility across global time zones. Comprehensive medical insurance coverage. Paid time off with a yearly minimum allowance and local public holidays. Annual personal development budget for books, courses, and coaching. Wellness budget to support fitness, health applications, and personal wellbeing. Access to regular health coaching sessions. Company-provided MacBook and work-from-home equipment as needed. Opportunity to shape engineering culture and influence the future direction of AI innovation. Chance to work on mission-driven technology impacting healthcare accessibility and delivery.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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