AI Product Manager

Ford Business Solutions

Chennai, Bengaluru

On-site

INR 1,800,000 - 3,000,000

Full time

3 days ago
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Job summary

Ford Business Solutions in Chennai is seeking a seasoned Product Manager to drive AI/ML-powered products. You will define the vision, strategy, and roadmap, translating business problems into clear requirements and owning the end-to-end lifecycle from discovery to launch.

Lead cross-functional teams with engineers and data scientists, run agile ceremonies, and measure success with KPIs such as model performance, adoption, latency, and business impact.

Qualifications

  • Bachelor of Engineering or B.Tech in CS/IT/Electronics or related discipline.
  • 5–7 years total experience, including 3 years in Product Management (AI/ML or data-driven products).
  • Hands-on experience building, fine-tuning, or deploying LLMs with portfolio/examples.
  • Practical knowledge of Python and ML frameworks (PyTorch, TensorFlow, Hugging Face) or LLM tooling (LangChain, LlamaIndex, vector DBs).
  • Experience managing multiple products/workstreams in a fast-paced environment.
  • Proficiency with Jira, Confluence, or equivalents.
  • Strong agile/scrum and cross-functional team leadership.
  • Excellent stakeholder management and written/verbal communication.

Responsibilities

  • Define and own the product vision, strategy, and roadmap for AI/ML-powered products and features.
  • Translate business problems and customer needs into clear product requirements, user stories, and acceptance criteria.
  • Manage the end-to-end product lifecycle: discovery, prioritization, development, launch, and post-launch iteration.
  • Run agile ceremonies (sprint planning, backlog grooming, retrospectives) and manage execution using Jira, Confluence, and similar tools.
  • Balance and manage multiple concurrent product workstreams/portfolios, prioritizing across competing stakeholder demands.
  • Define and track success metrics/KPIs (model performance, adoption, latency, cost-per-inference, business impact).
  • Partner cross-functionally with engineering, data science, design, legal/compliance, and business stakeholders.
  • Communicate roadmap, progress, and trade-offs clearly to leadership and stakeholders.

Skills

Product Management
Agile/Scrum
Stakeholder Management
Cross-functional Leadership
Communication

Education

Bachelor of Engineering (B.E.) or B.Tech in CS/IT/Electronics or related discipline

Tools

Jira
Confluence
Python
PyTorch
TensorFlow
Hugging Face
LangChain
LlamaIndex
Vector DBs
Google ADK

Job description

Role & responsibilities
Key Responsibilities
Product Management
  • Define and own the product vision, strategy, and roadmap for AI/ML-powered products and features.
  • Translate business problems and customer needs into clear product requirements, user stories, and acceptance criteria.
  • Manage the end-to-end product lifecycle: discovery, prioritization, development, launch, and post-launch iteration.
  • Run agile ceremonies (sprint planning, backlog grooming, retrospectives) and manage execution using Jira, Confluence, and similar tools.
  • Balance and manage multiple concurrent product workstreams/portfolios, prioritizing across competing stakeholder demands.
  • Define and track success metrics/KPIs (model performance, adoption, latency, cost-per-inference, business impact).
  • Partner cross-functionally with engineering, data science, design, legal/compliance, and business stakeholders.
  • Communicate roadmap, progress, and trade-offs clearly to leadership and stakeholders.
Hands-On Technical / AI-ML
  • Directly contribute to prototyping, fine-tuning, evaluating, and iterating on LLMs and other ML models (e.g., prompt engineering, RAG pipelines, fine-tuning, embeddings).
  • Collaborate closely with engineers/data scientists on data pipelines, model architecture trade-offs, and deployment strategy (MLOps).
  • Evaluate build-vs-buy decisions for foundation models, vector databases, and AI infrastructure tooling.
  • Stay current on the AI/LLM landscape (new model releases, techniques, regulatory/ethical considerations) and translate emerging capabilities into product opportunities.
Preferred candidate profile
  • Bachelor of Engineering (B.E.) or B.Tech Computer Science, Information Technology, Electronics, or related discipline.
  • 5 to 7 years of total professional experience, including 3 years in Product Management (AI/ML or data-driven products preferred).
  • Demonstrated hands-on experience building, fine-tuning, or deploying LLMs not just managing engineers who do so (e.g., portfolio, GitHub, published work, or specific project examples).
  • Practical knowledge of Python and common ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) or LLM tooling (Google ADK, LangChain, LlamaIndex, vector DBs).
  • Proven experience managing multiple products/workstreams simultaneously in a fast-paced environment.
  • Proficiency with product/project management and collaboration tools: Jira, Confluence, or equivalents.
  • Strong grasp of agile/scrum methodologies and experience running cross-functional agile teams.
  • Excellent stakeholder management, written, and verbal communication skills able to translate technical concepts for non-technical audiences and vice versa.
Perks and benefits
Preferred Qualifications
  • Domain experience in automotive, mobility, or manufacturing industries is an added advantage.
  • Solid understanding of NLP concepts, model evaluation metrics, prompt engineering, and RAG architectures is an added advantage.
  • Familiarity with responsible AI practices — bias mitigation, model governance, data privacy, and compliance frameworks.
  • Experience with cloud AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
  • Certifications in Product Management (CSPO, PMP) and/or AI/ML certifications are an added advantage.
What Success Looks Like in This Role
  • Shipped AI/LLM-powered features that measurably improve user outcomes and business KPIs.
  • A well-managed, transparent roadmap and backlog across multiple concurrent initiatives.
  • Strong trust from both business stakeholders (for product judgment) and technical teams (for technical credibility).
  • Continuous improvement of model quality metrics through direct hands-on involvement, not just delegation.

Location: Chennai

Work: Full-time

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