AI Technical Lead

About the role

The AI Technical Lead is responsible for designing and delivering scalable AI systems that enable intelligent applications across the organization. This role combines hands-on engineering, system architecture, and technical leadership to build production-grade machine learning and generative AI platforms.

Key Responsibilities

• Provide technical leadership and mentorship to a team of AI engineers.

• Establish engineering standards, coding practices, and architectural guidelines for AI system development.

• Lead design reviews, guide technical decision making, and resolve complex engineering challenges.

• Serve as a technical escalation point for AI system architecture and implementation.

• AI System Architecture:

  • Architect end-to-end AI systems including data pipelines, model training workflows, AI service layers, and scalable AI application infrastructure.

  • Design and implement AI-powered applications including large language model (LLM) systems and retrieval-based knowledge applications.

  • Define architecture patterns that support experimentation, rapid prototyping, and production deployment of AI capabilities.

  • Develop service-based architectures that enable AI functionality to be integrated across enterprise applications.

• AI Engineering & Development:

  • Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

  • Build reusable AI services and platform components that enable teams to rapidly develop and scale AI capabilities.

  • Implement evaluation, monitoring, and reliability systems to ensure consistent model performance.

  • Optimize AI pipelines for performance, scalability, and operational efficiency.

• Cloud & MLOps:

  • Design cloud-native infrastructure supporting AI and machine learning workloads.

  • Implement containerized AI services and automated deployment pipelines.

  • Support the development of scalable AI platforms that enable experimentation, model deployment, and operational monitoring.

  • Ensure AI systems follow best practices for reliability, observability, and cost management.

• Collaboration & Delivery:

  • Work closely with product managers, data engineers, and business stakeholders to identify and deliver high-value AI use cases.

  • Translate business requirements into scalable AI architecture and engineering solutions.

  • Partner with cross-functional teams to move AI solutions from pilots and experimentation into production environments.

  • Support initiatives that enable the organization to scale AI capabilities across multiple business domains.

• Responsible AI & Governance:

  • Promote responsible AI practices including transparency, fairness, and privacy considerations.

  • Implement safeguards and monitoring systems for AI applications operating in production.

  • Collaborate with security and compliance teams to ensure AI systems meet regulatory and organizational standards.

Required Experience

• 6+ years of experience in software engineering, machine learning engineering, and/or related AI/ML technical roles.

• Experience designing and deploying machine learning or generative AI systems.

• Strong programming experience in Python and modern backend technologies.

• Experience building distributed systems or cloud-native architectures.

• Experience implementing machine learning workflows or model deployment pipelines.

Preference For Additional Experience

• Experience with developing large language model (LLM) applications.

• Experience with retrieval-based AI systems or knowledge-driven applications.

• Experience with cloud platforms and modern DevOps practices.

• Mentoring engineers, leading technical initiatives, and/or serving as a technical lead.

• Experience working with large-scale data pipelines.

Pay Range

A good faith estimate of the current pay range is $118,506 - $177,758. The position is eligible for an annual incentive bonus (variable depending on company and employee performance).

Benefits

• Paid time off, paid holidays, community service and self-care days.

• Medical/dental/vision/pharmacy insurance.

• 401(k) matching and non-contributory plan.

• Life insurance.

• Short and long term disability.

• Education reimbursement.

• Employee Assistance Plan (EAP).

• Adoption assistance program.

• Paid family leave program.