Job Title: Lead AI Developer – Infrastructure Security Automation (L3)

Location: Reliance Corporate Park (RCP), Navi Mumbai

Working Hours: 9:00 AM – 6:00 PM

Mode of Interview: Face-to-Face or MS Teams

Headcount: 1 Position (L3 Level)

Position Summary

The Lead AI Developer – Infrastructure Security Automation (L3) is a principal technical lead role responsible for architecting and directing the delivery of production-grade AI systems, agentic platforms, and LLM-powered security capabilities. Operating within the Cyber Security Division, this role leads the design of advanced RAG systems, agentic state machines, model strategy (hosted and open-source fine-tuning/quantization), and evaluation frameworks. The Lead sets technical standards across Python/Java backend services, establishes threat modeling practices for AI workloads, and collaborates closely with security, DevOps, and infrastructure leadership to automate critical security operations

Requirements

Key Responsibilities

- AI Systems & Agentic Architecture: Architect and lead delivery of production AI systems and agentic platforms for vulnerability triage, remediation copilots, log/incident analysis, policy-as-code reviews, and natural-language query over security data.

- End-to-End LLM Strategy: Own LLM application architecture end-to-end: model selection, prompt strategy, RAG design, agent/tool orchestration, memory management, guardrails, and cost/latency optimization.

- Evaluation & Quality Frameworks: Design and implement evaluation frameworks including offline benchmarks, online A/B and shadow testing,



human-in-the-loop reviews, regression suites, and continuous quality monitoring for hallucination, accuracy, latency, and cost.

- Advanced RAG & Knowledge Systems: Lead RAG design covering ingestion pipelines, chunking and indexing strategies, embedding selection, hybrid retrieval (vector + lexical + re-ranking), and grounding patterns.

- Agentic System Engineering: Drive agentic system design using planner/executor patterns, tool use, multi-step workflows, error recovery, and safe action boundaries, while setting up agent observability and tracing.

- Responsible AI & Threat Modeling: Establish responsible-AI standards (prompt-injection defenses, PII handling, output validation, red-teaming, audit logging) and lead threat modeling for AI/LLM systems (adversarial prompt attacks, data poisoning, supply-chain risks).

- Model Optimization & Strategy: Evaluate hosted vs. open-source models; direct fine-tuning, distillation, and quantization strategies to balance accuracy, latency, cost, and data sovereignty.

- Engineering Leadership & Standards: Own production backend services in Python (and Java where required), define engineering standards (design reviews, testing,



observability), and oversee internal tool UIs/dashboards.

Candidate Profile & Qualifications

- Experience: 6 to 9 years of software engineering & AI developer leadership experience.

- Education: B.Tech or M.Tech in Computer Science, IT, or related technical field.

- Core Technical Skills:

- LLM & Model Expertise: Deep hands-on experience with LLM provider APIs (Anthropic, OpenAI, Azure OpenAI, Vertex AI) and open-source model stacks (Llama, Mistral, Qwen) including self-hosted serving, fine-tuning, and quantization.

- Orchestration & Agents: Strong command of orchestration frameworks (LangChain, LlamaIndex, LangGraph, Haystack); hands-on agentic experience (tool use, planner/executor patterns, state machines) and observability (LangSmith, Langfuse, Arize, Helicone).

- RAG & Vector Stores: Production RAG experience across ingestion pipelines, hybrid retrieval, re-ranking, and tuning with vector stores (pgvector, Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, Vertex AI Vector Search).

- Engineering & Backend: Production backend services in Python (and Java where required) alongside basic frontend/dashboard design.

- Mandatory Certifications (Any 1 required):

- CISSP, CCSP, Azure Security Engineer Associate (AZ-500), Azure AI Engineer Associate (AI-102), AWS Certified Security – Specialty, or GCP Qualified Cloud Security Engineer.

- Desirable Certifications:

- CISM, CEH, OSCP, GCP PMLE, AWS ML Specialty, CKA, Terraform Associate, or SC-100.

📌 Lead AI Developer – Infrastructure Security Automation (Mumbai)
🏢 Theomnihire
📍 Mumbai