Senior AI/ML Lead (Ref: 197881)

Operating in chemicals and related products manufacturing, our client is developing the AI capability required to improve product development, support operational growth, and respond to increasing customer demand. The organisation is progressing from exploratory use cases toward dependable, production-ready AI systems that connect advanced technology with measurable commercial and manufacturing outcomes.

Its environment presents an opportunity to influence how generative AI, data, and software engineering are applied within an established industrial context. The successful leader will help shape a practical AI function that can scale alongside the organisation's expanding product and business priorities.

The Senior AI/ML Lead will take ownership of the technical direction, delivery, and evolution of the organisation's AI platform. This role combines strategic architecture with hands-on engineering, requiring someone who can design production-grade LLM and generative AI solutions while remaining engaged in software, data, infrastructure, and deployment decisions.

Success will mean converting business priorities into an executable technical roadmap, delivering reliable AI capabilities, and establishing the engineering discipline needed for sustainable scale. You will guide developers, influence stakeholders across technical and non-technical functions, and operate as the senior day-to-day technical owner beneath a part-time CTO.

Scope extends across full-stack development, APIs, cloud infrastructure, databases, data pipelines, CI/CD, release automation, and platform reliability. As the organisation grows, the position offers a credible path toward broader leadership such as Head of AI, VP Engineering, or a future CTO-level remit.

The role is based in Boston, Massachusetts, with a requirement to attend quarterly in-person meetings at minimum. Candidates located in Massachusetts, particularly along the Worcester–Boston corridor, are strongly preferred.

• Set the technical vision and operating roadmap for the organisation's AI platform.
• Architect, build, and scale production-ready LLM and generative AI applications.
• Evaluate models, platforms, tools, and deployment patterns against business and engineering requirements.
• Remain hands-on across application code, APIs, services, infrastructure, and production troubleshooting.
• Lead technical delivery across front-end and back-end development where required.
• Design robust data architectures, database solutions, migrations, integrations, and data pipelines.
• Establish CI/CD, build, release, deployment automation, observability, and reliability practices.
• Translate commercial and operational objectives into sequenced technical initiatives and measurable outcomes.
• Provide day-to-day technical leadership, coaching, and decision support to developers.
• Define architecture principles, coding standards, review practices, and engineering governance.
• Partner with senior stakeholders to explain trade-offs, manage expectations, and maintain delivery alignment.
• Facilitate Agile ceremonies, including stand-ups, planning sessions, and delivery reviews.
• Convert product and business needs into clear user stories, acceptance criteria, and actionable work.
• Monitor platform performance, security, maintainability, and scalability as AI capabilities mature.

• Demonstrated experience taking LLM implementations from development through production operation.
• Strong practical background delivering generative AI products or capabilities used by real users or business processes.
• Deep understanding of AI/ML architecture, model integration, evaluation, deployment, and operational governance.
• Ability to design scalable systems that balance performance, reliability, cost, security, and speed of delivery.
• Hands-on full-stack engineering experience spanning front end, back end, APIs, cloud infrastructure, and deployment.
• Solid command of databases, data modelling, data architecture, migrations, integrations, and pipeline development.
• Experience building and improving CI/CD workflows, release tooling, build systems, deployment automation, and reliability engineering practices.
• Previous responsibility for leading engineers, allocating technical work, developing capability, and setting delivery standards.
• Proven ability to establish architecture conventions, engineering processes, and quality controls in a growing environment.
• Working experience with Agile delivery, including stand-ups, story creation, prioritisation, and iterative planning.
• Strong communication skills with the ability to make complex technical subjects clear to non-technical stakeholders.
• Commercial judgement and the ability to connect strategic priorities with pragmatic technical execution.
• Experience with Azure AI Services, Azure infrastructure, and Azure-based deployment environments is strongly preferred.
• US citizenship or permanent resident status through a green card is required.
• Availability to attend quarterly in-person meetings at minimum is required.
• Visa sponsorship is not available for this position.

• Hold meaningful ownership over the AI platform at a point when foundational architecture and engineering practices are still being shaped.
• Work on production generative AI initiatives with direct relevance to product development, customer demand, and organisational growth.
• Influence technical strategy across AI, application engineering, data, cloud infrastructure, and delivery operations rather than operating within a narrow specialist area.
• Work closely with senior decision-makers and help determine how AI capability is prioritised, funded, delivered, and measured.
• Build and mentor an engineering capability while establishing standards that can support future scale.
• Gain broad exposure to the commercial and operational application of AI within chemicals and related products manufacturing.
• Develop a clear progression platform toward Head of AI, VP Engineering, or future CTO-level responsibility.
• Operate from a Boston-based setting with regular in-person connection and substantial influence over the organisation's technical direction.

This opportunity suits a technically credible AI leader who enjoys moving between architecture, implementation, delivery management, and executive communication. The strongest candidates will bring the judgement to make high-quality decisions with incomplete information and the practical focus to turn those decisions into dependable systems.

Transferable experience is valued where it demonstrates production AI delivery, broad engineering capability, ownership of data and infrastructure, and effective leadership of technical teams. Applicants should be prepared to work with significant autonomy, engage directly with stakeholders, and attend quarterly in-person meetings; sponsorship is not available.