Senior Lead Product Manager AI Cybersecurity

Greetings from Netsach - A Cyber Security Company.

Job Description

We 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. You'll translate market and customer feedback into decisive product moves before competitors can blink.

Outcomes You'll Own

• Velocity 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 Cyber

security 

Job Location: Hyderabad - Onsite

Exp: 8-12yrs

Job Type: Fulltime

Interested candidates please share your resume at and please register at and send us your resume.

Required Experience

• 8–12 years in PM (or equivalent) delivering data-intensive or security products; exceptional 5–7 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 Have

• MSSP/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 You'll Do Strategy Roadmap

• Define and evolve roadmaps for Agentic SIEM, Autonomous SOC, One Agent (EDR/XDR), and

Threat 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, and

customer pain points.

AI-Native Productization

• Design agentic detection→decision→response loops with evaluation harnesses (precision/recall, drift checks, guardrails).
• Partner with research/engineering on model choices, prompts/policies, and explainability instrumentation.

Execution s Quality

• Translate 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 modern

AI-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 Depth

• Formalize L1→L3 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 Ecosystem

• Collaborate 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 Privacy

• Ensure 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 1–2 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 Competencies

• Strategic 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 You'll Move

• Effectiveness: 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 Build

• Speed 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 Model

• Hyderabad hub with close pairing to engineering; flexible hybrid for India-based candidates; relocation support available for the right talent.

Compensation

• Competitive salary + meaningful equity. We hire for impact and reward for outcomes.

What We Offer

• Build 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 You

Emily Jha

Netsach - A Cyber Security Company