Diversity Only | GenAI Product Manager | 5 days WFO | Mumbai | FMCG
Job Description
- Be a part of a strong and growing technical team of a major FMCG organization \n
- Growth prospects of moving up and managing teams \n\n
- MLOps & ML Lifecycle: Model development, deployment, monitoring, CI/CD, and automation. \n
- Tools & Frameworks: MLflow, Airflow, AzureML, Grafana, Kubernetes, GitHub, Docker, Python, PyTorch, TensorFlow, scikit‑learn. \n
- On‑Prem LLM Hosting & Inference: vLLM, Triton Inference Server, Hugging Face ecosystems, private model‑serving stacks. \n
- Agentic AI: PEE, PRA and similar frameworks using LangChain, LangGraph, LlamaIndex, AutoGen (or equivalents). \n
- AI/ML System Design: Production-grade architecture for ML and GenAI applications. \n
- Generative AI / LLM Architectures: Design and integration of LLM-driven and multimodal applications. \n
- Cloud & Data Engineering: Cloud-native systems (Azure, AWS, GCP), APIs, microservices, data pipelines. \n
- Databases: SQL and NoSQL systems; experience with REST APIs. \n
- Technology product management for AI/ML platforms. \n
- Ability to translate business needs into scalable AI solutions. \n
- Strong senior stakeholder engagement and executive communication. \n
- AI governance frameworks covering risk, compliance, security, auditability, and responsible AI practices. \n
- Strategic thinking and multi-year technology roadmap development. \n
- Ownership of enterprise-scale delivery and program governance. \n
- Risk assessment, mitigation, and issue resolution. \n
- Cross-functional stakeholder management across Business and IT. \n
- Financial, vendor, and commercial management. \n
- Team building, mentoring, and capability development. \n
- Change leadership and driving AI adoption at scale.
About Our Client
\n\nOur client is a large organization in the FMCG industry, specializing in household products. They are focused on leveraging data and analytics to enhance their market presence and operational efficiency.
\n\nJob Description
\n\nAI Platform & MLOps:
\n Own end‑to‑end MLOps architecture including model development, deployment, monitoring, retraining, CI/CD, versioning, experiment tracking, and observability. Ensure scalability, reliability, security, and cost efficiency in production.
\n AI Applications & Agentic AI:
\n Translate business needs into predictive, optimization, and generative AI solutions. Lead full lifecycle delivery of AI applications and design agentic systems with human‑in‑the‑loop controls. Ensure performance, accuracy, explainability, and user adoption.
\n AI Engineering & LLM Hosting:
\n Embed ML/GenAI into enterprise systems via API-first, cloud-native architectures. Lead on‑prem/private LLM hosting, including inference scaling, performance optimization, and secure integration. Oversee reliability engineering and technical debt management.
\n Governance & Responsible AI:
\n Establish AI governance frameworks around lifecycle management, compliance, auditability, bias mitigation, privacy, and responsible AI practices. Partner with security, risk, and legal teams.
\n Product Strategy & Leadership:
\n Serve as product owner for AI platforms. Define multi-year AI roadmaps aligned to business goals. Communicate AI strategy and progress to senior stakeholders and champion organization-wide AI adoption.
The Successful Applicant
\n\nRequired Skills & Competencies (Condensed & Structured)
\n Preferred Experience
\n 8-12 years of experience in AI/ML engineering, MLOps, or AI platform leadership roles.Technical Skills
Product & Leadership Skills
\nGovernance & Responsible AI
\nManagerial & Leadership Competencies
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