Senior Lead Product Manager AI Cybersecurity

Greetings from Netsach - A Cyber Security Company.Job DescriptionWe have an immediate requirement of Sr. Product Lead Manager with yrs of experience. Candidate will own strategy roadmap delivery for one or more of our core products, working closely with top management and product/engineering leaders in Hyderabad. The mandate: ship world-class features at lightning speed while upholding enterprise-grade reliability, security, and testability. Youll translate market and customer feedback into decisive product moves before competitors can blink.Outcomes Youll OwnVelocity with quality: Increase release cadence while maintaining enterprise readiness (SLOs, regression gates, rollback clarity).Measurable SOC impact: Improve MTTD/MTTR, reduce false positives, lift analyst efficiency, and optimize EPS/storage TCO.AI you can trust: Ship agentic workflows that are explainable, auditable, and safe (human-in-the- loop where needed).Market pull: Turn customer/partner feedback into shipped value in weeks, not quarters.Job Title: Senior/Lead Product Manager: Agentic AI Cybersecurity Job Location: Hyderabad - OnsiteExp: 8-12yrsJob Type: FulltimeInterested candidates please share your resume at and please register at and send us your resume.Required Experience812 years in PM (or equivalent) delivering data-intensive or security products; exceptional 57 years considered.Hands-on depth in SIEM/SOC/MDR/XDR workflows (detections, correlation/UEBA, case mgmt, SOAR/playbooks).Proven record of shipping fast in cloud-native stacks while keeping enterprise reliability (SLOs, canaries, rollback) intact.Comfort with AI/automation in production: evaluations, safety/guardrails, observability, and post- incident learning.Working knowledge of cybersecurity frameworks (NIST, MITRE ATTCCK), detection techniques, and anomaly detection.Practical AI/ML literacy: supervised/unsupervised methods, anomaly detection, prompt/policy design, evaluation (precision/recall, drift), and explainability.Cloud familiarity: AWS/Azure/GCP; security controls, data services, IAM.Excellent product writing, crisp prioritization, and stakeholder alignment across execs, eng, design, sales, and customers.(Education) BS/MS in CS/EE/InfoSec/Data Science or equivalent experience.Based in Hyderabad (or willing to relocate).Nice to HaveMSSP/MSP product motions; multi-tenant controls; usage-based or value-based pricing.Threat intel ecosystems (MISP/OTX/CERT advisories), Sigma/Kusto/KQL familiarity.Data governance C ethical AI: lineage, access controls, model risk management.Data lakehouse ops (Iceberg/Delta/Hudi), retention economics.Security/compliance exposure (SOC 2/ISO 27001), enterprise change mgmt.Certifications: CSPO/PSPO, Pragmatic PMC, or equivalent.Experience with BFSI, healthcare, pharma buyers and third-party risk reviews.What Youll Do Strategy RoadmapDefine and evolve roadmaps for Agentic SIEM, Autonomous SOC, One Agent (EDR/XDR), andThreat Data Hub.Convert market signals, customer councils, and competitive intel into clear priorities and trade-offs.Conduct market research and competitive analysis to identify emerging threats, AI trends, andcustomer pain points.AI-Native ProductizationDesign agentic detectiondecisionresponse loops with evaluation harnesses (precision/recall, drift checks, guardrails).Partner with research/engineering on model choices, prompts/policies, and explainability instrumentation.Execution s QualityTranslate complex security and AI requirements into clear product specs, PRDs, and user stories.Drive the full product lifecycle: ideation MVP GA iteration with feature flags, canaries, phased rollouts, and crisp rollback criteria.Work closely with engineering in Hyderabad to deliver rapid, high-quality releases using modernAI-driven dev tools.Balance speed to market with rigorous reliability testing for enterprise-grade deployments.Define measurable outcomes: faster detection, lower MTTR, analyst efficiency, and storage/TCO optimization.Enterprise Workflow DepthFormalize L1L3 automation, case mgmt, threat intel enrichment, and MITRE ATTCCK mapping.Shape data contracts/retention economics across lakehouse/warehouse (e.g., Iceberg/S3/ADLS), index tiers, and hot/cold paths.GTM s EcosystemCollaborate with Sales, Marketing, and Customer Success to create go-to-market plans, pricing, and positioning.Partner with GTM teams to ensure competitive positioning, sales readiness, and strong launches.Engage directly with CISOs, SOC managers, MSSPs, and industry partners to validate features and gather feedback.Compliance s PrivacyEnsure products meet regulatory and compliance standards (SOC 2, ISO 27001, GDPR, etc.).Build privacy-by-design, data minimization, and retention guardrails; support customer audits.Advocate for ethical AI practices, explainability, and model risk management.What Great Looks Like (30/60/G0)30 days: Product deep-dive; shadow SOC shifts and key customers; publish What Not To Break reliability notes; propose a 90-day win plan.60 days: Lock a focused roadmap slice; ship 12 needle-mover features with measurable SOC impact; stand up feature flags C phased rollouts.90 days: Land a marquee launch (or two) with references; show concrete TCO/MTTR wins; present next-two-quarters plan with clear KPIs.Key CompetenciesStrategic C analytical: converts fuzzy signals into sharp, prioritized bets.Customer-first: sits with CISOs/SOC leads; ships what shortens MTTD/MTTR.Decisive under speed: makes reversible decisions fast, irreversible ones with data.Execution rigor: obsessive acceptance criteria, test plans, post-mortems.Storytelling: crisp writing, compelling demos, clear trade-offs.Partnership mindset: aligns execs, eng, design, sales, and customers.KPIs Youll MoveEffectiveness: MTTD/MTTR, true-positive rate, false-positive reduction, auto-closure %, dwell-time reduction.Efficiency: EPS cost, storage $/TB-month, ingestion latency, runbook automation coverage.Quality: P0/P1 defects, rollback rate, upgrade success, availability/SLO adherence.Adoption/Growth: win-rate vs. incumbents, expansion by modules, time-to-value, NRR.How We BuildSpeed with safeguards: feature flags, dark launches, progressive rollouts, structured post- mortems.AI Safety C Explainability: human-in-the-loop for sensitive actions, transparent reasoning artifacts, customer-visible evaluation dashboards.Privacy C Compliance by design: DPIAs where needed, least-privilege access, auditable data flows, customer-controlled retention.Observability: golden paths, synthetic monitors, SLOs with burn-rate alerts, upgrade health KPIs.Customer-in-the-loop: CISO/SOC councils, design partner cycles, and field-ready betas.Written culture: PRDs that clarify trade-offs; dashboards that show impact.Location C Working ModelHyderabad hub with close pairing to engineering; flexible hybrid for India-based candidates; relocation support available for the right talent.CompensationCompetitive salary + meaningful equity. We hire for impact and reward for outcomes.What We OfferBuild genuinely market-leading AI security products used in high-stakes environments.Collaborative, builder culture with deep exposure to customers and execs.Competitive pay + performance incentives + equity, and budget for learning/certifications.Continuous learning and professional development in the fastest-moving space in cybersecurity.Thank YouEmily JhaNetsach - A Cyber Security Company