Company Overview Bridgestone Americas, Inc. (BSAM), headquartered in Nashville, Tennessee, and Bridgestone Europe, Middle East and Africa (BSEMEA), headquartered in Brussels, Belgium, operate collectively as a “Bridgestone West” strategic region. This region services the strategic business needs of teams across the Americas, Europe, Middle East and Africa. BSAM and BSEMEA are subsidiaries of Bridgestone Corporation, globally headquartered in Japan. Bridgestone and its subsidiaries develop, manufacture and market a wide range of Bridgestone, Firestone and associate brand products and solutions to address the needs of a broad range of customers and industries.
Job Category
Information Technology
Position Summary
A person has been identified as a preferred candidate for this role. While all applications will be reviewed, the hiring manager may choose not to hold interviews and select the preferred candidate. In this case, all internal applicants will be notified of the decision.
The Principal Applied AI Engineer leads the engineering of the artificial intelligence (AI),generative AI (GenAI) and agent solutions that the Business Insights & Advanced Analytics team builds for Bridgestone West, the company's Americas and Europe, Middle East and Africa (EMEA) business. The role sets the engineering standards every build follows, approves designs from other engineers, holds the engineering sign-off for go-live and defines the approach where no pattern exists. This is technical leadership without direct reports. The work is applied engineering, with no research component. The starting point is the AI already in production, including Bridgestone GPT, the company's internal GenAI assistant, and the Genie agents built on Databricks, the enterprise data platform. The role builds what comes next for business units across product development, manufacturing, supply chain, sales, retail, fleet and corporate functions: new agents that carry out multi-step work in business processes, and the shared components that let each business unit adopt AI faster. The role reports to the Director, Business Insights & Advanced Analytics. It works with business stakeholders, the enterprise data platform team, and engineers from the Global Capability Center (GCC) and delivery partners.
Responsibilities
- Set the technical direction for AI engineering on the team, and advise the Director and senior leadership on technology choices.
- Define the engineering standards every build follows: code review, testing, versioned prompts and retrieval patterns, automated evaluation, release and rollback practice, and the safe use of AI coding tools.
- Review and approve designs from GCC and partner engineers, review their code, and coach them to the team standard. Coach teammates in business intelligence and analytics as they take on AI and agent work.
- Own the architecture, releases and enhancements of the AI assistants and agents the team runs in production (today, Bridgestone GPT and the Genie agents).
- Design, build and maintain components of the team's AI solutions, including vector search indexes and endpoints, Model Context Protocol (MCP) servers, agents, AI workflows and predictive models.
- Ground solutions in governed data products and shared business definitions, and connect them to Bridgestone data and systems through approved application programming interfaces (APIs) and platform services.
- Run proofs of concept that answer a specific question quickly, provide feasibility assessments and effort estimates, and recommend a path for each opportunity: build, reuse, buy or do not use AI.
- Assess new models, frameworks and vendor tools as they are released, and recommend which to add to the approved platform services.
- Share the team's standards and reusable patterns with other Bridgestone teams that build AI, and contribute to architecture and technology reviews across IT.
- Build automated evaluation suites, tracing and regression checks, and require them to pass before every change goes live.
- Implement GenAI security guardrails: defense against prompt injection, prevention of data leakage and access controls on what a model or agent can read and do.
- Set cost, response time and reliability targets for each use case within the budget set by the budget owner, and choose models and designs to meet them.
- Take each solution through AI governance, Legal, Privacy and Security review, and give or withhold the engineering sign-off for go-live against the release criteria the role sets: evaluation results, documentation and security controls.
- Make solutions operable and measurable after go-live: runbooks, monitoring, reporting on adoption and agreed business measures, and feedback loops that improve them over time. Lead the technical response to production incidents and the review that follows.
- Publish components, agent definitions and architecture guidance as reusable assets, and require partner engineers to deliver code and documentation into Bridgestone repositories and hand over knowledge to the team before an engagement ends.
Minimum Qualifications
- Bachelor's degree in computer science, engineering or a related field, or equivalent practical experience.
- Minimum 10 years of production software engineering, mostly in Python, including atleast 5 years building and running machine learning or AI solutions in production, withat least 3 years on GenAI, large language model (LLM) or agent systems.
- At least 3 years of technical leadership at Lead or Staff level or equivalent, directingthe technical work of other engineers, including globally distributed teams.
- A record of setting engineering standards that other engineers build to, and ofshipping and maintaining production code that other teams depend on.
- Strong grounding in machine learning fundamentals and GenAI application patterns,including retrieval-augmented generation with embeddings and vector search, and amethod for measuring output quality.
- Hands-on experience with agent frameworks and orchestration, such as LangGraph, LangChain or an equivalent, covering tool use (including building and consuming MCPservers), memory and human-in-the-loop controls, with the judgment to recognize where an agent is the wrong answer.
- Experience with release and operations practice for models and LLM applications:automated evaluation suites, tracing, continuous integration and delivery (CI/CD),rollback, drift detection, and prompts under version control and testing.
- Experience with security and cost control for GenAI: prompt injection defense, dataleakage prevention, access control, and choosing designs against a budget.
- Hands-on experience with Databricks, including Databricks Genie and the DatabricksAI tooling, on Amazon Web Services (AWS) or Microsoft Azure.
- Experience with API design and integration against enterprise systems, and withgoverned data, where classification and access controls set what can be built.
- Daily use of AI coding tools in engineering, with the judgment to review and test whatthey produce.
- The ability to explain technical trade-offs to non-technical stakeholders in plainlanguage, choose the simplest solution that meets the need, write design decisionsand risk assessments that senior leadership can act on, and influence technicaldirection across teams and time zones without formal authority.
Nice to Have
- Experience with SAP source data. Many Bridgestone West use cases draw on SAP, thecompany's enterprise resource planning system.
- Experience in manufacturing, supply chain or another industrial domain.
- Experience delivering AI under regulatory requirements, for example the EU AI Act.
At Bridgestone, you are Free to Be
We believe people can only provide superior service and quality to others when they feel safe bringing their chosen version of themselves to work. We believe in championing all perspectives, individuals and teams because we understand the importance of seeing the world and our business through many different lenses. So, show us what you are made of, because who you are is what we need.
What we offer
At Bridgestone, what really matters is to foster co-creation opportunities and empowering you to be creative and curious to make mobility safer, more efficient, and more sustainable for future generations. Whatever role you fill, when you represent Bridgestone, you are a valued teammate, and part of our larger mission to “Serve Society with Superior Quality”, for that, we offer you more than just a competitive compensation; we will provide you:
- A supportive and engaging onboarding experience to ensure a smooth transition into our team.
- The opportunity to develop and grow, through training and regular mentorship.
- Corporate Social Responsibility activities.
- A truly global, dynamic and challenging work environment.
- Agility and work/life effectiveness and your long-term well-being.
- An effective and inclusive team.
Bridgestone is proud to be an Equal Employment Opportunity employer. It is our policy to consider all individuals for employment based on their unique merit and without regard to age, color, national origin, citizenship status, physical or mental disability, race, religion, gender, sex, sexual orientation, gender identity and/or expression, genetic information, veteran status, or any other characteristic protected by federal, state or local law.
Employment Eligibility If hired, a Form I-9 Employment Eligibility Verification must be completed at the start of employment. Temporary work authorization or the need for sponsorship may disqualify you from employment.
