Summary
What you’ll impact
The Vice President, AI / Machine Learning Engineer will lead the design and development of applied AI solutions within the organization’s AI Hub, driving technical direction and delivering production‑ready capabilities for software engineering. This hands‑on technical leader will collaborate with engineering and business stakeholders to improve the software development lifecycle and mentor engineers across architecture, reliability, and responsible AI adoption.
Responsibilities
What you'll do
- Lead the design and development of applied AI solutions, providing hands-on technical leadership for machine learning and artificial intelligence products.
- Bring strong knowledge of Applied AI, LLMs, fine tuning, model evaluation, and approaches to building fit-for-purpose models, copilots, and agents for engineering use cases.
- Conduct technical research, prototyping, and experimentation to evaluate model and tooling approaches, and translate findings into actionable recommendations and implementation plans.
- Partner with engineering and business stakeholders to understand priorities, workflows, and opportunities, and help define success measures that demonstrate developer and business impact.
- Bring expertise in applying AI to improve the software development lifecycle and support builders, designers, and developers with secure, scalable, and production-ready capabilities.
- Contribute to the achievement of Application Development objectives by mentoring engineers, promoting strong engineering practices, and supporting high-quality delivery across architecture, reliability, and responsible AI adoption.
Requirements
What you’ll bring
- Bachelor's degree in Computer Science, Data Engineering, or a related field or the equivalent combination of education and experience required.
- 5-9 years of experience in software development required; experience in the securities or financial services industry is a plus.
- Advanced experience, preferably 8+ years, in applied AI/ML, model development, and software engineering, including experience building and deploying production solutions.
- Ability to operate as a hands-on technical lead, collaborating with engineers and partners while helping drive design, implementation, and delivery decisions.
- Strong understanding of enterprise software practices, MLOps / LLMOps, evaluation approaches, and how to create secure, scalable, and sustainable AI solutions.
- Ability to communicate technical ideas effectively and work across a range of audiences, including engineers, product partners, and business stakeholders.