Live opening · Posted 7 days ago

Product Manager

Comviva · Bengaluru, Karnataka, India (Hybrid)
Linkedin No
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At a glance

The key details from the original listing.

Posted 7 days ago
CompanyComviva
LocationBengaluru, Karnataka, India (Hybrid)
Work modeNo
SourceLinkedin
Listed7 days ago

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About the role

Description supplied by the original job listing.

Role: AI Product Manager
Location: Gurgaon/Bangalore
Experience: 9-14 years
Key Accountabilities
Define and own the product roadmap for MobiLytix AIx — predictive and prescriptive model lifecycle capabilities across MobiLytix.
Define product requirements for real-time model scoring infrastructure and edge-based execution.
Establish model registry, versioning and deployment governance frameworks.
Define model health monitoring capabilities including performance tracking, drift detection and optimisation feedback loops.
Define model-level explainability artefacts and technical performance visibility for predictive and prescriptive models.
Define and own the product roadmap for design-time and runtime agent capabilities within MobiLytix.
Establish product requirements for agent authoring tools, workflow builders and reusable agent design patterns.
Define product capabilities for conversational and low-code agent configuration interfaces.
Define and own the runtime orchestration engine for multi-step decision workflows.
Establish decision traceability and execution transparency mechanisms across agent workflows.
Define guardrails, policy frameworks and governance requirements for autonomous decision execution.
Translate business AI use cases from Module PMs into reusable agent templates, orchestration patterns and model-backed decision capabilities.
Define optimisation loops that integrate predictive and prescriptive model outputs into agent execution without owning model development.
Collaborate with Module PMs to enable predictive, prescriptive and agentic capabilities required for business AI use cases without owning business logic.
Ensure model and agent capabilities align with platform abstraction and extensibility principles.
Monitor advancements in AI, autonomous systems, orchestration engines, optimisation tooling and agent development platforms.
Partner with engineering and data science teams to translate model infrastructure and agent execution requirements into scalable implementation.
Mandatory Skills
8+ years of product management experience in AI, ML, optimisation, orchestration or decision-driven SaaS platforms, with demonstrable depth across both model lifecycle and agentic / orchestration capabilities.
Strong conceptual understanding of predictive and prescriptive modelling, optimisation systems, autonomous agent frameworks and workflow engines.
Experience defining enterprise-grade model lifecycle, governance and monitoring capabilities.
Experience defining product requirements for both configuration interfaces and runtime execution engines.
Experience with real-time model scoring, deployment patterns and decision-driven product capabilities.
Experience integrating predictive or optimisation model outputs into higher-level decision and orchestration systems.
Ability to translate AI and optimisation concepts into structured product requirements.
Strong systems thinking and architectural reasoning capability.
Experience collaborating closely with data scientists, engineering and cross-functional product teams.
Strong stakeholder management and cross-functional alignment capability.
Experience supporting enterprise AI capability discussions.
Desirable Skills
Experience with next-best-action or next-best-offer modelling frameworks and integration into orchestration workflows.
Exposure to conversational AI, low-code workflow builders or agent authoring platforms.
Familiarity with model observability, drift detection, ML monitoring tools and policy enforcement or guardrails in AI systems.
Exposure to reinforcement learning, optimisation engines, decision intelligence platforms or compute-to-data execution models.
Experience in decisioning, marketing automation or real-time engagement platforms.
Experience working in global enterprise SaaS environments.

Work arrangement
No

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