The posting
ABOUT TEKION:
Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.
ROLE OVERVIEW
We are looking for a technically strong Senior Product Manager with hands-on experience building and launching AI-powered B2B enterprise products.
You will own product strategy, roadmap, and execution for intelligent products and platform capabilities that solve complex customer and operational problems. Working closely with Engineering, AI/ML, Design, and Data teams, you will take capabilities from discovery and prototyping through production deployment, adoption, and continuous improvement.
This role requires strong technical judgment, an understanding of enterprise workflows, and demonstrated AI product development experience—not just familiarity with AI tools.
KEY RESPONSIBILITIES
PRODUCT STRATEGY & OWNERSHIP
- Own the product vision, strategy, and roadmap, aligning enterprise customer needs with business priorities.
- Lead customer discovery to identify high-value problems and determine where AI, deterministic workflows, or a combination of both provides the best solution.
- Translate complex requirements into clear PRDs, user journeys, feature specifications, user stories, and measurable acceptance criteria.
- Prioritize initiatives based on customer impact, technical feasibility, dependencies, risk, and delivery effort.
- Own the product lifecycle from concept and validation through launch, adoption, and ongoing optimization.
AI PRODUCT DEVELOPMENT
- Lead the development of AI-powered experiences, including LLM-based applications, retrieval-augmented generation (RAG), and agentic workflows.
- Partner with AI/ML and Engineering teams on model selection, grounding, tool integrations, orchestration, and human-in-the-loop controls.
- Define agent behaviors, intent routing, skill specifications, policy configurations, permissions, and fallback mechanisms.
- Establish evaluation frameworks and curated golden datasets to assess accuracy, task completion, reliability, safety, and edge-case handling.
- Define release criteria and production monitoring, balancing output quality, latency, inference cost, and user experience.
- Use customer feedback, evaluation results, and production insights to continuously improve AI capabilities.
TECHNICAL PRODUCT LEADERSHIP
- Collaborate with Engineering on scalable services, Java-based microservices, Kafka event pipelines, and agentic platform integrations.
- Review system designs, API specifications, data models, and integration flows to clarify requirements and evaluate trade-offs.
- Define API requirements, data contracts, authentication and authorization needs, and failure-handling expectations.
- Partner with platform and data teams on schemas, instrumentation, observability, and integration dependencies.
- Ensure enterprise requirements—including security, privacy, access controls, reliability, scalability, and auditability—are incorporated into product decisions.
- Participate in technical troubleshooting and root-cause discussions with engineering teams.
DELIVERY, MEASUREMENT & ADOPTION
- Own backlog prioritization and partner with engineering Scrum teams to deliver outcome-focused releases.
- Define and track KPIs across adoption, task success, customer satisfaction, operational efficiency, AI quality, and cost.
- Validate solutions through prototypes, experiments, pilot programs, and customer feedback.
- Drive launch readiness, stakeholder communication, user enablement, and change management.
- Communicate roadmap decisions, dependencies, risks, and technical trade-offs clearly to technical and non-technical stakeholders.
REQUIRED SKILLS & QUALIFICATIONS
- 5+ years of Product Management experience, with ownership of technically complex products.
- B2B enterprise product management experience is a must, including experience addressing complex workflows, integrations, and the needs of multiple stakeholders.
- Proven experience building and shipping AI/ML-powered products into production, with direct ownership of discovery, requirements, evaluation, launch, and measurable outcomes.
- Strong practical understanding of LLMs, RAG, agentic workflows, tool calling, and AI limitations and failure modes.
- Experience defining AI evaluation criteria, test scenarios, quality benchmarks, and production feedback loops.
- Strong technical fluency across distributed systems, microservices, event-driven architectures, APIs, and data platforms.
- Hands-on experience working with RESTful APIs, webhooks, authentication mechanisms, and enterprise integrations.
- Ability to read and discuss architecture diagrams, API documentation, data models, and technical specifications with engineering teams.
- Strong analytical and structured problem-solving skills, with experience defining KPIs and using data to guide product decisions.
- Excellent written communication, stakeholder management, and cross-functional leadership skills.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.
GOOD TO HAVE
- Experience building campaign management or CRM products.
- Experience with Model Context Protocol (MCP), agent orchestration, and reusable AI tools or skills.
- Experience authoring PRD-as-Code artifacts, including intent definitions, skill specifications, and policy configurations.
- Familiarity with Java-based services, Kafka, cloud infrastructure, and AI observability tools.
- Experience with AI security, privacy, prompt-injection risks, and responsible AI practices.
- Ability to use SQL, API testing tools, and workflow automation tools to validate assumptions and investigate issues.
- Prior experience in automotive retail, dealer technology, or enterprise operational workflows.
Current Tekion Employees: Please apply via the Internal Job Board in Ashby.
Note: Tekion recently transitioned to a new recruiting tool and we appreciate your patience and feedback as we adjust to our new system!
Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.
For more information on our privacy practices, please refer to our Applicant Privacy Notice here https://tekion.com/legal/privacy/applicant-and-candidate-privacy-notice.
Important: Tekion will only contact candidates from an @tekion.com http://tekion.com email address or through our applicant tracking system ([email protected]). We may also work with authorized recruiting partners from time to time. Tekion and its recruiting partners will never ask you to pay fees or send money for applications, interviews, training, or onboarding. If you receive a message that seems suspicious, please do not respond or share personal or financial information.
