Product Manager

Job description

Job Description: Experience: 3–6 Years **Location:** India (Onsite/Hybrid) **Role Overview** We are seeking an experienced **Technical Product Manager (TPM)** to lead end-to-end delivery of large-scale **AI/GenAI programs** , including agentic workflows, ML platforms, and enterprise AI solutions. The role requires strong **program governance, cross-functional leadership, and technical understanding of AI architectures** . **Key Responsibilities** **1. Stakeholder Management** - Act as **single point of contact** for clients, leadership, and cross-functional teams - Drive alignment between product, engineering, data science, and business teams **2. Technical Program Ownership** - Oversee design and delivery of: - GenAI / LLM-based solutions (RAG, agentic workflows) - Data pipelines, ML models, and AI platforms - Cloud-native deployments (AWS/Azure/GCP) - Ensure adherence to **AI architecture, scalability, and best practices** including governance and lifecycle management **3. Execution & Delivery Excellence** - Manage **multi-stream programs** with distributed teams (Data Scientists, ML Engineers, AIOps, DevOps) - Track delivery against timelines, budget, and quality benchmarks - Proactively identify risks, dependencies, and mitigation plans - Drive **Agile / Hybrid delivery models** (Scrum, SAFe, etc.) **4. Team Leadership & Capability Building** - Lead cross-functional teams and mentor program managers, leads, and engineers - Build AI delivery capability across areas such as GenAI, ML engineering, and data platforms - Drive continuous improvement, knowledge management, and best practices **5. Compliance & Responsible AI** - Ensure adherence to **Responsible AI standards, data privacy, and governance frameworks** - Drive risk mitigation related to bias, hallucination, and model governance **Required Skills & Qualifications** **Experience** - 3-6 years of experience in **technology delivery/program management** - 5+ years managing **AI / ML / GenAI programs at scale** **Technical Skills** - Strong understanding of: - AI/ML lifecycle, & GenAI architectures - LLMs, RAG, agentic AI frameworks - Cloud platforms (AWS, Azure, GCP) - Experience with data ecosystems, APIs, and enterprise integrations **Product Management Skills** - Proven experience managing **large, multi-million-dollar programs** - Expertise in governance frameworks, KPIs, dashboards, and reporting - Strong risk & dependency management **Leadership & Soft Skills** - Excellent stakeholder management and executive communication - Strong problem-solving and decision-making abilities - Ability to operate in **high-pressure, delivery-driven environments** **Preferred Qualifications** - PMP / PgMP / Agile certifications - Exposure to industries like BFSI, Insurance, or Healthcare **Responsibilities: Key Responsibilities 1. Stakeholder Management** - Act as **single point of contact** for clients, leadership, and cross-functional teams - Drive alignment between product, engineering, data science, and business teams **2. Technical Program Ownership** - Oversee design and delivery of: - GenAI / LLM-based solutions (RAG, agentic workflows) - Data pipelines, ML models, and AI platforms - Cloud-native deployments (AWS/Azure/GCP) - Ensure adherence to **AI architecture, scalability, and best practices** including governance and lifecycle management **3. Execution & Delivery Excellence** - Manage **multi-stream programs** with distributed teams (Data Scientists, ML Engineers, AIOps, DevOps) - Track delivery against timelines, budget, and quality benchmarks - Proactively identify risks, dependencies, and mitigation plans - Drive **Agile / Hybrid delivery models** (Scrum, SAFe, etc.) **4. Team Leadership & Capability Building** - Lead cross-functional teams and mentor program managers, leads, and engineers - Build AI delivery capability across areas such as GenAI, ML engineering, and data platforms - Drive continuous improvement, knowledge management, and best practices **5. Compliance & Responsible AI** - Ensure adherence to **Responsible AI standards, data privacy, and governance frameworks** - Drive risk mitigation related to bias, hallucination, and model governance Qualifications: Bachelor's/Master's in any stream 3-6 years