This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Artificial Intelligence/Machine Learning Engineer based in United States.
This is a hands-on engineering leadership role focused on scaling teams and production-grade AI/ML and LLM systems. You will lead engineers across a central platform team and multiple delivery pods, helping teams move quickly while maintaining strong technical and quality standards. The role combines people leadership, engineering governance, AI architecture review, and day-to-day delivery support. You will help establish consistent approaches to agent quality, production readiness, code reviews, evaluation, and development practices. Working closely with platform leadership and a mix of internal and contractor engineers, you will remove blockers without creating unnecessary layers of approval. This is an opportunity to shape how AI engineering is delivered at scale in a fast-moving, collaborative environment.
Accountabilities:
- Lead engineers across the central platform team and delivery pods, effectively coordinating teams that include both internal employees and contractors.
- Establish and maintain engineering standards covering code quality, AI agent quality, review practices, definition of done, and production readiness.
- Partner with platform leadership to establish and scale a consistent paved path covering templates, pipelines, evaluation practices, and other reusable engineering foundations.
- Ensure delivery teams consistently adopt established platform patterns and engineering standards while maintaining appropriate flexibility for individual initiatives.
- Unblock engineering teams on a daily basis, helping delivery pods maintain momentum without becoming an unnecessary gatekeeper.
- Oversee contractor performance and contribute to the contractor-to-employee conversion pipeline in partnership with the relevant sourcing organization.
- Review AI agent architectures, prompts, and evaluation suites to maintain a credible technical quality bar across teams.
- Balance technical leadership and people management in a flat, fast-moving environment, remaining close enough to the work to guide engineers effectively.
Requirements:
- 8+ years of professional engineering experience, including at least 3 years managing engineers who have delivered AI, machine learning, or LLM-based systems into production.
- Proven experience managing blended teams consisting of both contractors and employees while maintaining consistent engineering quality and delivery standards.
- Strong enough hands-on AI/ML and LLM expertise to confidently review agent architectures, prompting approaches, evaluation frameworks, and production-readiness decisions.
- Demonstrated ability to lead engineering teams while remaining technically engaged and capable of making sound architectural and quality decisions.
- Comfortable operating as a player-coach in a flat, fast-paced organization, with a collaborative leadership style focused on enabling teams rather than building unnecessary hierarchy.
- Strong communication, prioritization, problem-solving, and people leadership skills, with the ability to remove blockers and keep teams moving toward delivery.
- Experience in healthcare or another regulated industry is a plus, particularly where quality, reliability, and responsible technology practices are important.
- Experience scaling an engineering team from fewer than 10 people to 30+ is a plus.
- Experience with AI platforms and Azure Machine Learning is relevant to the role.
Benefits:
- Competitive benefits package including healthcare coverage, basic life insurance, and short- and long-term disability insurance, according to applicable benefit plans.
- Fully remote work within the United States.
- Opportunity to work alongside experienced professionals in a collaborative and open-door environment.
- Exposure to large-scale, globally impactful technology projects and opportunities to expand your expertise.
- Internal learning opportunities through meetups, conferences, workshops, Udemy access, and language courses.
- Company-paid professional certifications to support continued technical and career development.
- Opportunities for internal mobility across different domains and technology areas.
- Hands-on exposure to cutting-edge AI, machine learning, and digital transformation initiatives.
- Opportunity to lead and influence AI engineering practices across multidisciplinary teams and delivery environments.
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.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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