AI and Analytics Product Manager

Ford Motor; Chennai; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Ford Motor in Chennai seeks an AI/Analytics Product Manager to own the end-to-end product lifecycle for enterprise AI, analytics, and data products. Translate business needs into scalable features, define KPIs, and drive roadmaps with strong stakeholder collaboration.

You will partner with Engineering, Data Science, and Security teams to deliver AI-powered solutions, maintain governance, and ensure measurable business impact across Ford’s digital ecosystem.

Qualifications

• Experience managing AI, analytics, or data products across the product lifecycle.
• Strong product strategy, roadmap planning, prioritization, stakeholder management, and execution skills.
• Experience translating business requirements into product features and technical capabilities.
• Strong customer-centric product development and outcome-based delivery.
• Experience defining KPIs, OKRs, success metrics, and product analytics.

Responsibilities

• Own the end-to-end product strategy, roadmap, and execution for AI & analytics capabilities.
• Translate business problems into scalable AI, analytics, and data products to improve customer experience and business value.
• Lead product discovery, prioritization, and backlog management using Agile methodologies.
• Collaborate with Engineering, Data Science, Data Engineering, Security, Privacy, UX, Architecture, and Business stakeholders to deliver enterprise-grade AI solutions.
• Define product KPIs and experimentation strategies, and continuously optimize using data-driven insights.
• Drive adoption of AI-powered automation and intelligent decision-making across the platform.
• Ensure AI products comply with security, privacy, governance, and responsible AI standards.

Skills

AI product management

Analytics product management

Data products

Product strategy

Roadmap planning

Prioritization

Stakeholder management

Execution

Translating requirements

Customer-centric

OKRs and KPIs

Product analytics

Agile/Scrum

Backlog management

User stories

Sprint planning

Release planning

Cross-functional collaboration

Engineering & data teams

Agentic AI

LangGraph or similar

LLM orchestration

Tool calling

RAG architectures

Vector databases

Embeddings

Semantic search

Prompt engineering

Grounding strategies

AI governance

Data science lifecycle

Statistical analysis

ML concepts

Experimentation

Structured data

SQL

Data visualization

KPIs development

Business intelligence

AI deployment

Tools

BigQuery

SQL

Cloud analytics platforms

Data pipelines

APIs

Event-driven architectures

Data governance

MLOps

CI/CD

Docker

Kubernetes

GCP

Job description

AI/Analytics Product Manager

Required Skills

Product Management

• Experience managing AI, Analytics, or Data products throughout the product lifecycle.
• Strong product strategy, roadmap planning, prioritization, stakeholder management, and execution skills.
• Experience translating business requirements into product features and technical capabilities.
• Strong understanding of customer-centric product development and outcome-based delivery.
• Experience defining KPIs, OKRs, success metrics, and product analytics.

Agile Delivery

• Hands-on experience with Agile/Scrum methodologies.
• Experience managing product backlogs, user stories, sprint planning, release planning, and incremental product delivery.
• Strong collaboration across cross-functional engineering, architecture, data, and business teams.

Agentic AI & Generative AI

• Experience designing, building, and managing autonomous AI agents, including single-agent and multi-agent systems.
• Hands-on experience with agentic frameworks such as LangGraph or similar orchestration frameworks.
• Knowledge of LLM orchestration, tool calling, function calling, planning, reasoning, workflow decomposition, and AI agent lifecycle management.
• Experience building AI solutions using Retrieval-Augmented Generation (RAG) architectures.
• Knowledge of vector databases, embeddings, semantic search, hybrid retrieval, prompt engineering, grounding strategies, and context optimization.
• Experience implementing AI-powered automation, self-healing workflows, anomaly detection, automated root-cause analysis, and intelligent remediation capabilities.
• Understanding of Responsible AI, AI governance, model evaluation, observability, and monitoring.

Data Science & Analytics

• Strong understanding of Data Science lifecycle, statistical analysis, machine learning concepts, predictive analytics, and experimentation.
• Experience working with structured and unstructured data to derive actionable business insights.
• Knowledge of feature engineering, model evaluation, model performance monitoring, and AI/ML solution lifecycle.
• Experience partnering with Data Scientists to operationalize AI and machine learning models into production.
• Strong analytical skills with expertise in SQL, data visualization, KPI development, and business intelligence.
• Experience leveraging analytics to drive product decisions and measure business impact.

Data & Cloud Technologies

• Experience with BigQuery, SQL, cloud-native analytics platforms, and modern data architectures.
• Understanding of data pipelines, data engineering concepts, APIs, event-driven architectures, and data governance.
• Experience working on Google Cloud Platform (GCP) is preferred.
• Familiarity with MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and AI deployment best practices.

Leadership Expectations

• Strong strategic thinking with the ability to balance long-term vision and execution.
• Excellent communication and stakeholder management skills across business and technology organizations.
• Demonstrated ability to lead cross-functional teams without direct authority.
• Passion for innovation, continuous learning, and delivering measurable business outcomes through AI and analytics.
• Hands‑on mindset with the ability to work closely with engineering and data science teams to shape solution architecture, validate technical approaches, and drive successful product delivery.

Key Responsibilities

• Own the end‑to‑end product strategy, roadmap, and execution for AI & Analytics capabilities supporting the Digital Account & Consent Platform.
• Translate business problems into scalable AI, analytics, and data products that improve customer experience, operational efficiency, and business value.
• Lead product discovery, prioritization, roadmap planning, and backlog management using Agile methodologies.
• Collaborate with Engineering, Data Science, Data Engineering, Security, Privacy, UX, Architecture, and Business stakeholders to deliver enterprise‑grade AI solutions.
• Define product KPIs, success metrics, experimentation strategies, and continuously optimize product performance using data‑driven insights.
• Drive adoption of AI-powered automation, predictive analytics, and intelligent decision‑making capabilities across the platform.
• Ensure AI products comply with enterprise security, privacy, governance, responsible AI, and data management standards.
• Stay current with emerging AI technologies and identify opportunities to accelerate innovation across Ford’s Digital ecosystem.

Preferred Qualifications

• Experience with Customer Identity, Digital Account, Consent Management, Customer Data Platforms (CDP), or Customer 360 solutions.
• Experience delivering enterprise AI or GenAI products at scale.
• Knowledge of LLMOps, MLOps, AI observability, and production AI systems.
• Familiarity with ML frameworks, fine‑tuning approaches (PEFT/LoRA), and model lifecycle management.
• Experience building AI-powered recommendation, personalization, search, or intelligent automation solutions.
• Knowledge of enterprise architecture, cybersecurity, privacy regulations, and data governance.

Experience Level

Mid Level