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Dharmendra Verma

Dharmendra Verma

AI Product Manager

Talent
PuneMember since April 21, 2026
Generative AILLM, ML, RAGAgentic SystemsMCPn8nAI EvaluationAzureAzure AIGoogle FirebaseFirebase StudioC#PythonSQLJavaScriptREST APIsDockerMicroservicesCI/CDAzure App InsightData AnalyticsGrafanaGoogle AnalyticsA/B testingMetric definitionJIRAAzure developsConceptboardFIGMAAI Product ManagementProduct Strategy & RoadmapStakeholder ManagementBacklog ManagementAgile & Scrum LeadershipUser Experience & DiscoveryGo2Market StrategyMetrics-Driven DeliveryResponsible AI & GovernanceCompliance & GovernanceNIST AI RMFProduct Market Fit
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Generative AILLM, ML, RAGAgentic SystemsMCPn8n

About

AI Product Leader with 6+ years of experience architecting and launching 0→1 AI-native B2B solutions in high-stakes environments. Expert in GenAI, RAG, and Agentic Systems with a proven track record of driving 15-50% efficiency gains through hands-on technical leadership and rapid prototyping. Skilled in 'vibe-coding' and rapid iteration using Claude Code, Firebase Studio, and n8n to align engineering and design teams early.

Led the 0→1 launch of RAG-based copilots on Azure AI, managing the full lifecycle from customer discovery to production. Experienced in collaborating directly with executive leadership to define product roadmaps and market validation strategies.

Experience

Product Manager — COMOS Product Suite at Siemens Industry Software (India) Pvt. Ltd. (2017-01 – 2026-01)

Led product strategy, roadmap, and cross-functional delivery across 4 COMOS products — COMOS AI, DDMS, COMOS enterprise web platform, and mobile field operations — serving global plant engineering customers

  • COMOS AI Chatbot | MVP → Production: Delivered end-to-end the department's first customer-facing AI application — an Azure AI chatbot using Semantic Search and RAG that surfaces contextual plant-engineering guidance. Instrumented a rich analytics layer tracking queries, intent trends, and response quality — driving continuous tuning and giving leadership real-time adoption visibility. 15% productivity lift, > 65% first-try acceptance, establishing the foundation for AI adoption across the COMOS suite.
  • COMOS DDMS | Metadata ML Service: Architected and shipped an ML service that cut complex metadata tagging effort by 70% and unblocked large-scale brownfield migrations. Owned the full lifecycle — training-data strategy, fine-tuning DistilBERT on customer taxonomies, and productizing a confidence-scored suggestion layer with human-in-the-loop review.
  • COMOS Mobile | New MRO Use Case (Tour Maintenance): Spotted that field engineers were limited to single-asset work orders while real MRO required multi-asset inspection tours. Repurposed an underutilized backend capability for mobile and designed a zero-training UX — unlocking a new use case that drove new customer acquisition and lifted existing-customer satisfaction.
  • COMOS DDMS | SharePoint Integration: Eliminated dependency on COMOS-specific document workflows by enabling native SharePoint integration — cutting checkout setup time by 90% and improving workflow efficiency 10×. Reframed document management from a configuration burden into a leverage point on customers' existing stack.
  • COMOS Web | Search Experience Redesign: Rebuilt search around discoverability research with plant engineers — barcode scanning, customer-configurable terminology rules, AND/OR logic, and a persistent global search bar. +30% search success rate, −30% time-to-find.
  • COMOS Web | Enterprise SSO: Partnered with customer IT and security to replace Windows/LDAP with OIDC-based SSO (Okta, Azure AD), resolving a compliance blocker and enabling external-supplier onboarding — unblocking stalled enterprise deployments.
  • COMOS Web | Event-Driven Integration (Kafka): Led replacement of degrading webhook notifications — which required manual server resets under load — with a Kafka pub/sub event service for real-time integration with external enterprise systems. +20% customer adoption for MRO workflows.
  • COMOS Mobile | Sync Performance: Diagnosed data-sync latency as the #1 field-engineer complaint and led the fix across mobile, backend, and QA teams — sync time −40%, CSAT 60% → 80%.

Software Engineer & Technical Lead at Siemens (2007-06 – 2017-12)

Software Engineer at NIIT Technologies (2005-12 – 2007-06)

Education

Postgraduate Diploma in Advanced Computing – CDAC

Bachelor of Technology in Technology – CSJM University

Skills

AI Product Manager

Reviews

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