Senior Applied AI Engineer II

Saint-Gobain Innovation North America is looking for a hands-on Senior Applied AI Engineer to help turn R&D, industrial, scientific, and business challenges into production-ready AI and digital solutions. In this onsite role in Northborough, MA, you will work across the full lifecycle, from framing high-value problems to deploying AI/ML and generative AI systems that teams can adopt and sustain.

You will design architectures, build reliable software and data components, and integrate enterprise solutions with the support of IT, data, MLOps, cybersecurity, architecture, and platform teams. The position also emphasizes responsible AI use, with guardrails, evaluation, source traceability, and qualified human review as part of how systems operate in real environments.

What you’ll do

• Partner with domain experts and users to discover and frame high-value problems, including workflows, decisions, operating conditions, and available data.
• Translate ambiguous needs into technical requirements, solution architectures, delivery plans, and measurable outcomes.
• Design human-and-AI workflows where accountable domain experts retain key decisions.
• Design, build, integrate, test, deploy, and support production components for AI/ML, data, automation, and software using Python, APIs, data pipelines, Git-based development, CI/CD, documentation, and observability.
• Engineer generative AI and large language model systems using RAG, vector search, prompt and orchestration patterns, agentic workflows, evaluation, guardrails, source traceability, qualified human review, and reliability monitoring.
• Integrate solutions with enterprise environments, including enterprise data, databases, dashboards, web applications, and on-premises or cloud infrastructure while following approved services.
• Evaluate quality, reliability, usability, limitations, and workflow impact.
• Protect sensitive information by following applicable information-protection, security, legal, export-control, and data-governance requirements, and communicate when AI is not the right fit.
• Drive deployment through demonstrations, user adoption, documentation, training, operational handoff, and continuous improvement.
• Communicate progress, tradeoffs, risks, value, and next steps to technical and business audiences.
• Create reusable reference architectures, templates, evaluation methods, integration patterns, and deployment playbooks.
• Provide technical guidance and mentor junior engineers, data scientists, interns, and project contributors.

What you bring

• Bachelor’s degree plus 12 years of experience, or Master’s plus 7 years, or PhD plus 3 years in Software Engineering, Data Science, Industrial Engineering, Mechanical Engineering, or a related technical discipline.
• Hands-on experience delivering production software, data, AI/ML, analytics, automation, or generative AI solutions in industrial, enterprise, R&D, or customer-facing settings beyond notebooks and proofs of concept.
• Strong Python and software-engineering fundamentals: maintainable code, modular design, APIs, data pipelines, testing, Git-based development, and technical documentation.
• Proven ability to engineer LLM systems using RAG, vector search, orchestration patterns, agentic workflows, evaluation, guardrails, and reliability monitoring.
• Experience integrating into enterprise data sources and environments, including security and data-governance controls.
• Ability to lead stakeholder discovery, map workflows, and convert ambiguous requirements into architectures, delivery plans, success measures, and adoption plans.
• Capability to explain architecture, risks, tradeoffs, limitations, and value to scientists, engineers, industrial teams, business stakeholders, IT, cybersecurity, and leadership.
• Technical leadership across ambiguous projects, with sound engineering judgment, cross-team coordination, and flexible scope as conditions change.
• Experience moving prototypes into sustained use, including monitoring, operational handoff, adoption, continuous improvement, and measurable workflow impact.
• Experience mentoring less-experienced engineers, data scientists, interns, or contributors in engineering, documentation, evaluation, and deployment practices.

Technologies you’ll work with

Python, APIs, data pipelines, Git-based development, CI/CD, observability, RAG, vector search, prompt and orchestration patterns, agentic workflows, evaluation, guardrails, source traceability, qualified human review, reliability monitoring

Preferred qualifications

• Experience with cloud platforms, containers, CI/CD, MLOps or LLMOps, observability, or regulated/high-confidentiality data environments.
• Experience in manufacturing, industrial R&D, scientific R&D, process engineering, or technical consulting environments.
• Familiarity with specializations such as computer vision, optimization, simulation workflows, IoT, laboratory or plant data, knowledge graphs, or enterprise search.
• Ability to learn new scientific/manufacturing/business domains quickly (materials-science experience helpful but not required).

Compensation and bonus

• The national pay range for this position is $102,000 to $158,000 per year.
• In addition to base salary, this position is eligible for an annual bonus.
• The targeted bonus amount is 13% of base salary based on company and individual performance measures.
• Total Target Cash (base pay and annual bonus) is $115,260 to $178,540.
• Bonus payments are variable compensation and can vary based on company and individual performance, so they are not guaranteed.

Benefits

• Health and Well-being
• Medical, Prescription Drug, Vision, and Dental Insurance
• Healthcare Saving Account and Flexible Spending Account options
• LiveWell Wellness Program
• Employee Assistance Program (EAP)
• Paid Time Off and Paid Parental Leave
• 401(k) with Company Match
• Retirement Accumulation Plan (RAP) Cash Balance Pension Plan
• Company-provided Life Insurance, AD&D, Short-Term Disability
• Voluntary employee and dependent life insurance, Long-Term Disability, Critical Illness and Accident Insurance
• Group Legal
• Identity Theft Protection
• Auto and Home Insurance
• Pet Insurance and Discounts
• Back-up Child and Elder Care
• PerkSpot Employee Discount Program
• Volunteer Day