Senior Product Manager - Central Data Repository & Data Platform AI

Aligned to InMobi’s vision, one of the priorities of the CEO’s office is to look at Enterprise system & AI transformation with consolidation of products & business systems for - unlocking productivity, realizing efficiencies, streamlining critical business process flows and integrating cross-system architecture to achieve a lean and agile organizational set up.

Our Product members in the Product Team have a strong understanding of the company’s underlying business, data, product and process challenges in reporting frameworks, translating them into long term sustainable product solutions that are applicable across InMobi’s expanding & diversified business, finance, people & strategy units. This team will work across a spectrum of enterprise systems and internal products building end to end features and capabilities that help establish a fully integrated blueprint of company’s data architecture and system landscape. Our AI SPM will need to go deep and understand business operations across the End-to-end value chain to identify ‘product modifications, enhancements and system integrations’ keeping the larger inter-connected ecosystem in mind. They need to be extremely agile and on top of technology & be AI hands-on. They need to think big, multi-task, lead cross-functional initiatives and be able to deal with ambiguity with a positive attitude, in fact, thrive in it to deliver positive timely outcomes.

• AI Product Vision & Strategy: Define and drive end-to-end AI product vision, roadmap, and GTM strategy. Own PRDs, user journeys, wireframes, and product analysis. Lead architecture decisions with AI Engineering, oversee implementation, testing, iteration, and launch.
• Applied ML & AI Expertise: Strong working knowledge of supervised, unsupervised, and reinforcement learning, neural networks, and NLP/NLU - with the ability to evaluate trade-offs and guide engineering toward optimal solutions.
• MLOps & Model Lifecycle: Own the full AI product lifecycle - data strategy, model training, validation, deployment, production monitoring, drift detection, and retraining. Define and enforce MLOps best practices.
• Modern AI Architectures: Deep familiarity with LLMs, RAG, agentic workflows, multi-agent systems, and multimodal architectures. Evaluate build-vs-buy decisions and assess emerging AI frameworks for enterprise use.
• AI Prototyping & Hands-on Building: Independently build functional prototypes and POCs using low-code tools or code-first approaches. Architect and build agents, evaluation pipelines, and demo-ready solutions.

• Data Strategy & Architecture: Own data pipelines, quality frameworks, annotation workflows, storage architecture, and governance. Identify gaps, biases, and scalability risks in datasets.
• Model Evaluation & Experimentation: Define evaluation frameworks using precision, recall, F1, ROC-AUC alongside business KPIs. Design A/B testing strategies for AI/ML iterations.
• Context Engineering: Design how AI systems interpret user intent - managing retrieval logic, prompt engineering, memory layers, and context window optimization.
• Ethical AI & Compliance: Champion fairness, transparency, and accountability. Lead compliance with GDPR, EU AI Act, and establish internal guardrails and responsible AI practices.
• Translational Leadership: Bridge data science, engineering, design, business, and executive stakeholders - translating technical constraints into business impact narratives.
• Adaptive Product Strategy: Move beyond deterministic roadmaps to adaptive learning loops. Prioritize based on real-time user behavior and model performance data.
• Risk Management: Identify and mitigate technical failures, security vulnerabilities, data privacy risks, and AI-specific failure modes (hallucinations, adversarial attacks, data leakage).

• Overall experience of 12+ years with a ‘make it happen’ attitude
• 10+ years in Product Management with demonstrated ownership of AI/ML products from 0-to-1 and at scale
• Proven track record of writing outstanding AI PRDs, user journeys, wireframes, and end-to-end product analysis
• Build product design from scratch and drive AI Engineering teams through implementation, testing, and launch. Must be AI hands-on - able to build agents, prototypes, and evaluation frameworks independently
• Deep empathy for business user behaviour and ability to translate needs into data-driven solutions and automations at enterprise scale 
• Excellent communication and stakeholder management - set clear expectations with senior leadership, call out dependencies, and influence across geographically dispersed and culturally diverse teams 
• Demonstrated ability to mentor junior PMs and raise the bar on product thinking and AI literacy within the organization 
• Thrive in ambiguous, fast-moving environments and deliver high-quality outcomes with minimal guidance 
• Strong bias for logical, data-backed decision-making with attention to detail and strategic altitude 
• Formulate compelling points of view on hard problems, drive senior stakeholder alignment, and execute decisively

At InMobi, culture isn’t a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences.

We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make.

We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program.

InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace.

Visit https://www.inmobi.com/company/careers to better understand our benefits, values, and more!