Project Manager

Precision Technologies; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

Precision Technologies is seeking a results-driven AI Product Manager to lead end-to-end planning, delivery, and governance of AI/ML projects and enterprise AI initiatives in the United States. You will define product vision, roadmaps, success metrics, and prioritize use cases in alignment with business goals.

You will coordinate cross-functional teams including AI/ML engineers, data scientists, cloud architects, UX designers, and QA, ensuring responsible AI practices, regulatory compliance, and

Responsibilities

• Lead end-to-end planning, execution, delivery, and monitoring of AI/ML projects, AI products, Generative AI applications, and enterprise AI transformation programs.
• Define AI product vision, strategy, roadmap, business requirements, success metrics, and delivery priorities in alignment with organizational objectives.
• Identify, evaluate, and prioritize AI use cases based on business value, technical feasibility, customer needs, implementation complexity, and expected ROI.
• Coordinate cross-functional teams, including AI/ML Engineers, Data Scientists, Data Engineers, Software Engineers, Cloud Architects, UX Designers, QA Engineers, and business stakeholders.
• Manage project scope, schedules, budgets, resource allocation, dependencies, risks, issues, milestones, and delivery commitments.
• Translate business requirements into PRDs, epics, user stories, acceptance criteria, functional specifications, and implementation plans.
• Oversee AI/ML development lifecycle activities, including data preparation, model development, experimentation, evaluation, deployment, monitoring, and continuous improvement.
• Manage Generative AI initiatives involving LLMs, RAG, Prompt Engineering, AI Agents, vector databases, model integration, and enterprise AI application development.
• Collaborate with technical teams to evaluate AI architectures, cloud AI services, model selection, data readiness, integration requirements, scalability, latency, and operating costs.
• Establish KPIs, OKRs, adoption metrics, model performance indicators, quality benchmarks, and business outcome measurements to assess AI initiative success.
• Ensure responsible AI practices, data privacy, security, regulatory compliance, model governance, bias mitigation, explainability, and risk management throughout delivery.
• Facilitate Agile ceremonies, sprint planning, backlog refinement, stakeholder reviews, executive presentations, status reporting, and release planning.
• Manage vendor relationships, third-party AI platforms, external partners, procurement activities, and technology evaluations where applicable.
• Drive product adoption, user feedback collection, change management, training, and continuous enhancement of AI-powered products and solutions.

Job description

Employment Type: W2 / Full-Time

Location: United States (Onsite / Hybrid / Remote – Based on Client Requirement)

Visa: Open to all work-authorized candidates except H1B

Key Responsibilities:

• Lead end-to-end planning, execution, delivery, and monitoring of AI/ML projects, AI products, Generative AI applications, and enterprise AI transformation programs.
• Define AI product vision, strategy, roadmap, business requirements, success metrics, and delivery priorities in alignment with organizational objectives.
• Identify, evaluate, and prioritize AI use cases based on business value, technical feasibility, customer needs, implementation complexity, and expected return on investment.
• Coordinate cross-functional teams, including AI/ML Engineers, Data Scientists, Data Engineers, Software Engineers, Cloud Architects, UX Designers, QA Engineers, and business stakeholders.
• Manage project scope, schedules, budgets, resource allocation, dependencies, risks, issues, milestones, and delivery commitments.
• Translate business requirements into product requirements documents (PRDs), epics, user stories, acceptance criteria, functional specifications, and implementation plans.
• Oversee AI/ML development lifecycle activities, including data preparation, model development, experimentation, evaluation, deployment, monitoring, and continuous improvement.
• Manage Generative AI initiatives involving LLMs, RAG, Prompt Engineering, AI Agents, vector databases, model integration, and enterprise AI application development.
• Collaborate with technical teams to evaluate AI architectures, cloud AI services, model selection, data readiness, integration requirements, scalability, latency, and operating costs.
• Establish KPIs, OKRs, adoption metrics, model performance indicators, quality benchmarks, and business outcome measurements to assess AI initiative success.
• Ensure responsible AI practices, data privacy, security, regulatory compliance, model governance, bias mitigation, explainability, and risk management throughout delivery.
• Facilitate Agile ceremonies, sprint planning, backlog refinement, stakeholder reviews, executive presentations, status reporting, and release planning.
• Manage vendor relationships, third-party AI platforms, external partners, procurement activities, and technology evaluations where applicable.
• Drive product adoption, user feedback collection, change management, training, and continuous enhancement of AI-powered products and solutions.

Contact:

Mahesh Kyadari, Lead – Talent Management Team