AI Product Manager

Laiba Technologies LLC; Redmond (WA); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Laiba Technologies LLC is seeking an AI Product Manager/TPM to lead the strategy, roadmap, and delivery of AI-powered products. You will bridge business objectives with data science, engineering, and UX to build scalable and responsible AI solutions.

The ideal candidate brings strong product management experience and deep knowledge of AI, ML, GenAI, LLMs, and enterprise governance. You will define vision, prioritize investments, and drive successful AI adoption.

Qualifications

• Bachelor's degree or equivalent in CS/Engineering/Data Science/Business or related field.
• 8 years of Product Management experience.
• 3 years leading AI, ML, GenAI, or Data-driven products.
• Experience with enterprise-scale digital products, Product strategy and roadmap development.
• Understanding of Machine Learning, Deep Learning, NLP, and Generative AI.
• Experience with LLMs, Prompt Engineering, RAG, Vector Databases, and AI Agents.
• Knowledge of AI evaluation frameworks and experimentation methodologies.
• Understanding of AI architecture, APIs, integrations, and MLOps concepts.
• Ability to define KPIs and product success metrics.
• Excellent communication and storytelling skills.
• Stakeholder management and executive communication.
• Ability to influence executive stakeholders and cross-functional teams.

Responsibilities

• Define and execute the AI product vision, strategy, and roadmap aligned with business objectives.
• Identify high-value AI and GenAI opportunities across business functions and customer journeys.
• Create PRDs and translate business challenges into scalable AI-powered solutions.
• Use ADO to maintain product backlogs, user stories, acceptance criteria, and release plans.
• Establish success metrics, KPIs, and measurable business outcomes for AI initiatives.
• Collaborate with AI Architects/ Engineers to define model requirements and evaluation criteria.
• Drive development of AI/ML, LLM, RAG, Copilot, and Agentic AI solutions.
• Define model performance metrics including accuracy, precision, recall, latency, and user satisfaction.
• Ensure AI products are scalable, secure, and production ready.
• Drive end-to-end product lifecycle management from concept to deployment and continuous improvement.
• Ensure compliance with Responsible AI, security, privacy, and regulatory requirements.
• Define AI governance frameworks, guardrails, bias mitigation strategies, and model monitoring processes.
• Establish monitoring approaches for model drift, hallucinations, and operational risks.

Skills

Executive communication

Stakeholder management

Product storytelling

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Business, or related field

Tools

Azure AI Foundry

OpenAI

Microsoft Copilot ecosystem

Databricks

Vertex AI

Job description

Position: AI Product Manager/ TPM

Location: Redmond, WA - Remote, USA

AI Product Manager to lead the strategy, roadmap, and delivery of AI-powered products and capabilities.

This role will bridge business objectives, customer needs, data science, engineering, and user experience teams to build scalable, responsible, and high-impact AI solutions.

The ideal candidate combines strong product management expertise with a solid understanding of Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, Large Language Models (LLMs), and enterprise AI governance.

The role requires defining product vision, prioritizing investments, measuring business impact, and ensuring successful adoption of AI capabilities.

Key Responsibilities

• Define and execute the AI product vision, strategy, and roadmap aligned with business objectives.
• Identify high-value AI and GenAI opportunities across business functions and customer journeys.
• Create Product Requirement Documents (PRDs), Translate business challenges into scalable AI-powered solutions describing business impact, technical feasibility, and customer value.
• Use ADO to maintain product backlogs, user stories, acceptance criteria, and release plans.
• Establish success metrics, KPIs, and measurable business outcomes for AI initiatives.
• Collaborate with AI Architects/ Engineers to define model requirements and evaluation criteria.
• Drive development of AI/ML, LLM, RAG, Copilot, and Agentic AI solutions.
• Define model performance metrics including accuracy, precision, recall, latency, and user satisfaction.
• Ensure AI products are scalable, secure, and production ready.
• Drive end-to-end product lifecycle management from concept to deployment and continuous improvement.
• Ensure compliance with Responsible AI, security, privacy, and regulatory requirements.
• Define AI governance frameworks, guardrails, bias mitigation strategies, and model monitoring processes.
• Establish monitoring approaches for model drift, hallucinations, and operational risks.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Business, or related field.
• 8 years of Product Management experience.
• 3 years leading AI, ML, GenAI, or Data-driven products.
• Experience managing enterprise-scale digital products, Product strategy and roadmap development.
• Understanding of Machine Learning, Deep Learning, NLP, and Generative AI.
• Experience with LLMs, Prompt Engineering, RAG, Vector Databases, and AI Agents.
• Knowledge of AI evaluation frameworks and experimentation methodologies.
• Understanding of AI architecture, APIs, integrations, and MLOps concepts.
• Ability to define KPIs and product success metrics.
• Excellent communication and storytelling skills.
• Stakeholder management and executive communication.
• Ability to influence executive stakeholders and cross-functional teams.

Preferred Qualifications

• Experience building Copilots, Agentic AI applications, or enterprise GenAI platforms.
• Familiarity with Azure AI Foundry, OpenAI, Microsoft Copilot ecosystem, Databricks, or Vertex AI.
• Experience with AI governance, Responsible AI, and enterprise compliance frameworks.
• Knowledge of experimentation, A/B testing, telemetry, and product analytics.