We’re looking for a AI Lead to own the AI architecture, strategy, and execution for our enterprise security product. You’ll lead a small team, design our Model Gateway, govern prompts, qualify models, and ensure AI makes us smarter without making us less trustworthy.

What You’ll Do
• Own the Model Gateway: provider registry, qualification suite, durable task queue, fallback strategies.
• Enforce prompt governance: thin prompts, thick code, pseudonymisation, broken chains, split audit.
• Build AI compute inside a hardware-isolated enclave: embedding encoder, prompt renderer, response validator.
• Drive business context extraction: closed questions into fixed schemas, promotion gates, confidence rules.
• Lead investigation and hunting: planner loop with typed tools, deterministic verdicts, narrative generation.
• Evaluate new architectures, track the model landscape, and recommend when to add or remove providers.
• Hire, mentor, and lead a team of AI engineers.

What You Bring
• 8+ years in software engineering, 3+ years leading AI/ML teams in production.




• Deep LLM integration experience (Bedrock, Azure OpenAI, Vertex, Anthropic, OpenAI).
• Robust understanding of model limitations: hallucination, prompt injection, data leakage, non-determinism.
• Production experience with embeddings and vector search (pgvector or similar).
• Experience building systems where AI is not on the critical path determinism, auditability, reproducibility.
• Security mindset: you understand why a security product can’t trust a model to make a decision.
• Enterprise deployment experience: customer-managed environments, sealed enclaves, compliance (SOC 2, ISO 27001).
• Excellent written communication for design docs and governance.

Nice to Have
• Confidential computing / secure enclaves (Nitro, Azure Confidential VMs, GCP Confidential Space).
• Security product background (SIEM, EDR, CSPM, attack path management).
• Graph databases (Apache AGE, Neo4j).
• MITRE ATT&CK; familiarity.
• Open-so

📌 AI Lead (Hyderabad)
🏢 vikat ai
📍 Hyderabad