SecOps Architect I

o9solutions; Bengaluru; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

o9solutions in Bangalore, India, is hiring a Senior AI Security & MLSecOps Architect for an on-site role. You will lead security for the GenAI platform, securing AI agents, models, and integrations across 500+ customer environments.

The role focuses on building ML-driven security capabilities, threat detection, and autonomous security agents to protect enterprise planning systems and data pipelines. Experience with AI security and compliance is required.

Responsibilities

• Own the security architecture for o9's GenAI platform - ensure every AI agent, model, and integration is governed and auditable.
• Design and enforce agent identity controls, permission scoping, and behavioural baselining for production AI agents.
• Architect the AI Bill of Materials (AIBOM/SBOM) pipeline with model provenance and dependency scanning.
• Secure retrieval-augmented generation pipelines with allowlisting, isolation, and PII scrubbing.
• Define security review gates for AI integrations with enterprise systems and enforce token governance.
• Align AI security controls to ISO 42001, NIST AI RMF, MITRE ATLAS, and OWASP Top 10 for LLM Apps.

Job description

Transforming the Future of Enterprise Planning

At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions-even billions-in value leakage, we help businesses plan smarter and faster.

This not only enhances operational efficiency but also reduces waste, leading to better outcomes for both businesses and the planet. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

Transforming the Future of Enterprise Planning

At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions - even billions - in value leakage, we help businesses plan smarter and faster. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

Senior AI Security & MLSecOps Architect

Technology - AI Trust & Cyber Security | Bangalore, India | Full-Time

We are looking for a Senior AI Security & MLSecOps Architect to lead the next generation of AI-native security at o9. You will own two parallel missions: securing o9's GenAI platform and agentic AI ecosystem from emerging threats, and building AI/ML-driven capabilities that transform how our security operations detect, predict, and respond to adversarial activity across 500+ customer environments.

Our security platform ingests 22 billion events per month across 176,000+ hosts, 266 Kubernetes clusters, and 3,042 cloud accounts. The intelligence hidden in that telemetry remains largely unmined. Simultaneously, o9's GenAI platform is scaling rapidly - production AI agents, RAG pipelines, MCP tool integrations, and autonomous planning workflows that introduce a fundamentally new class of security risk. This role exists to address both.

What you’ll do for us

AI Platform Security & Governance

Own the security architecture for o9's GenAI platform - ensuring every AI agent, model, and integration is governed, auditable, and stoppable.

AI Agent Security Architecture:

Design and enforce agent identity controls, permission scoping, and behavioural baselining for all production AI agents. Build UEBA-style models that detect when an agent deviates from learned tool-call patterns, data-access scope, or egress destinations - triggering automated containment via kill-switch controls.

AI SBOM & Model Risk Management:

Architect the AI Bill of Materials (AIBOM/SBOM) pipeline - model provenance verification, hash integrity, dependency scanning, and supply chain trust for every LLM, embedding model, and agent deployed to production. Ensure no model reaches production without a signed inventory entry.

RAG & Prompt Security:

Design security controls for retrieval-augmented generation pipelines - source allowlisting, tenant isolation, PII scrubbing, indirect prompt injection detection, and embedding anomaly monitoring. Secure the retrieval boundary as the highest-risk component in the AI stack.

Cross-System AI Integration Security:

Define security review gates for AI integrations with enterprise systems (ticketing, DevOps, observability, MCP servers). Enforce token governance, credential rotation, blast-radius modelling, and data classification for every cross-system data flow.

AI Governance & Compliance:

Align AI security controls to ISO 42001, NIST AI RMF, MITRE ATLAS, and OWASP Top 10 for LLM Applications. Maintain audit trails for every model decision. Support EU AI Act and DPDPA compliance evidence generation.

AI/ML Engineering for Security Operations

Build ML models and autonomous agents that convert raw security telemetry into predictive, actionable defence.

Threat Detection & Anomaly Modelling:

Build, fine-tune, and deploy ML models that detect anomalous patterns, novel attack variations, and stealthy TTPs mapped to MITRE ATT&CK across the full telemetry corpus - including predictive weak-point analysis that scores which assets or identities are most likely to be exploited next.

Autonomous Security Agents:

Architect and build the autonomous security agent layer - threat-hunting agents, vulnerability-management agents, configuration-audit agents, and incident-response agents operating at machine speed. Define full observability: reasoning traces, tool calls, results, and outputs - tamper-proof and forensically auditable.

LLM-Powered SOAR & Enrichment:

Evolve SOAR playbooks from rule-based automation to ML-driven, context-aware orchestration - integrating LLM-based enrichment into triage and response decision loops. Reduce false-positive rates (target: Identity Threat Scoring: Build ML-powered identity risk scoring on top of identity protection telemetry - reducing identity threat risk scores and maintaining them autonomously through continuous model retraining from red team findings.

Security