eNGINE builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with eNGINE.

Role Overview

eNGINE is hiring two Senior Product Managers to lead the end-to-end implementation of AI and Machine Learning solutions—especially LLM-driven capabilities—into real business workflows.

These roles are focused on execution, not theory. You will own the delivery of AI-powered products from initial concept through production deployment, ensuring they are successfully embedded into day-to-day operations and drive measurable impact. This includes working across multiple teams in a pod-based, high-throughput delivery model, where speed, quality, and scalability all matter.

We are specifically looking for individuals who have hands-on experience applying AI/LLMs to solve business problems and have successfully brought those solutions into production environments.

Responsibilities

End-to-End AI Product Delivery

• Own the lifecycle of AI/ML products from ideation, design, development, and deployment into production
• Drive implementation of LLM-powered solutions that enhance internal workflows and user productivity
• Partner with engineering and data teams to ensure scalable, reliable AI integrations
• Make tradeoff decisions balancing model performance, cost, latency, and user experience

Product Ownership & Execution

• Manage and prioritize product backlogs across multiple AI initiatives
• Write clear user stories, acceptance criteria, and product specifications for AI-driven features
• Ensure continuous delivery of value through iterative releases and rapid feedback loops
• Assess release readiness and maintain a high bar for quality and usability

Agile / Factory-Style Delivery

• Operate within a structured, pod-based delivery model focused on throughput and execution
• Lead agile ceremonies including sprint planning, backlog grooming, and retrospectives
• Track team velocity and identify opportunities to optimize delivery efficiency
• Coordinate across teams to ensure consistent and predictable release cycles

AI / LLM Implementation

• Translate business needs into practical AI use cases leveraging LLMs and ML models
• Collaborate on prompt design, model selection, evaluation, and iteration
• Ensure AI solutions are usable, reliable, and embedded into real workflows
• Monitor and improve model performance and user outcomes post-deployment

Product Strategy & Roadmap

• Define and manage a near-term roadmap focused on AI enablement across the organization
• Align product initiatives with business goals and measurable outcomes
• Clearly communicate priorities, tradeoffs, and progress to stakeholders

Customer & Data-Driven Insights

• Engage with end users to understand how AI can improve their workflows
• Define and track KPIs related to product adoption, performance, and impact
• Use data to continuously refine product direction and prioritization

Stakeholder Management

• Act as a central point of coordination across product, engineering, data science, and business teams
• Provide clear and consistent communication on progress, risks, and delivery outcomes

Qualifications

• 5+ years of Product Management experience in software development environments
• Proven experience delivering AI/ML products, with strong exposure to LLM-based solutions
• Demonstrated ability to take products from concept through production deployment
• Experience implementing technology directly into business workflows or operational environments
• Strong experience in agile, pod-based, or high-throughput delivery models
• Ability to manage multiple concurrent initiatives and backlogs
• Experience writing product requirements, user stories, and specifications

Preferred Experience

• Hands-on experience with platforms such as OpenAI, Hugging Face, or similar LLM ecosystems
• Familiarity with prompt engineering, evaluation frameworks, and AI observability
• Experience with cloud platforms like Amazon Web Services or Microsoft Azure
• Background in data-driven or analytics-heavy product environments
• Exposure to CI/CD pipelines and modern DevOps practices

Next Steps

No C2C, relocation, referral candidates, or sponsorship for this role.

About eNGINE

eNGINE is a Technical Solutions firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Successful outcomes start and finish with eNGINE.

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