Senior AI Developer – InfraSec Automation (L2)

Theomnihire; Mumbai; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Theomnihire is seeking a Senior AI Developer – InfraSec Automation (L2) to design, build, and deploy production‑grade, LLM‑powered features for infrastructure security workflows. You will develop end‑to‑end RAG pipelines and agentic workflows, writing production Python and Java code.

The role integrates AI capabilities into security platforms, SIEMs, and cloud infrastructure, with a focus on guardrails, secure prompts, and scalable microservices.

Qualifications

• 4–6 years of core software engineering and AI development experience.
• B.Tech or M.Tech in Computer Science, IT, AI/ML, or a related field.
• Hands‑on experience with LLM provider APIs (Anthropic, OpenAI, Azure) and related frameworks.

Responsibilities

• AI Feature Development: design and ship LLM‑powered security assistants for vulnerability summaries and log triage.
• Prompt Engineering & Schemas: create prompts and structured‑output schemas; iterate with evaluations.
• End‑to‑End RAG Pipelines: build chunking, embeddings, vector store integration, retrieval tuning.
• Microservices & API Development: Python microservices wrapping LLM providers and backend in Java as needed.
• LLM Evaluation & Quality Control: implement evaluation harnesses and regression suites.
• AI Security & Guardrails: implement prompt‑injection mitigations, PII redaction, access controls.
• Ecosystem Integrations: connect AI services with SIEMs, scanners, ticketing platforms.
• Automation & MLOps: automate data prep, embeddings refresh, eval runs, health checks.
• Cross‑Functional Collaboration: work with security, DevOps and infra teams to scale AI solutions.

Skills

Python

Backend

LLM Frameworks

Vector Databases

RAG Pipelines

Security Controls

Education

B.Tech or M.Tech in CS/IT/AI‑ML

Tools

LangChain

LlamaIndex

LangGraph

Haystack

pgvector

Pinecone

Weaviate

Chroma

FAISS

Job description

Senior AI Developer – InfraSec Automation (L2)

Job Title: Senior AI Developer – InfraSec Automation (L2)

Working Hours: 9:00 AM – 6:00 PM

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

Headcount: 2 Positions

Position Summary

The Senior AI Developer – InfraSec Automation (L2) is a hands‑on technical role focused on designing, building, and deploying production‑grade, LLM‑powered features and AI tools for infrastructure security workflows. Working within the Cyber Security Division, you will bridge AI engineering and security operations by developing end‑to‑end RAG pipelines, agentic workflows, automated remediation assistants, and evaluation harnesses. You will write production‑quality Python and Java code, implement security controls around AI services, and integrate automated AI capabilities natively into security platforms, SIEMs, and cloud infrastructure.

Requirements

Key Responsibilities

• AI Feature Development: Design, build, and ship LLM‑powered security assistants that support vulnerability summarization, log triage, remediation recommendations, policy reviews, and natural‑language queries over security data.
• Prompt Engineering & Schemas: Develop prompt templates, system prompts, and structured‑output schemas (JSON schema, function calling), continuously iterating via offline and online evaluations.
• End‑to‑End RAG Pipelines: Implement Retrieval‑Augmented Generation (RAG) pipelines including chunking strategies, embeddings management, vector store integration, retrieval tuning, and grounding.
• Microservices & API Development: Build and operate Python‑based AI microservices and APIs (using FastAPI/Flask) that wrap LLM providers (Anthropic, OpenAI, Azure OpenAI, Vertex AI) and open‑source models, alongside supporting backend services in Java where required.
• LLM Evaluation & Quality Control: Implement evaluation harnesses, golden datasets, and regression suites to measure LLM performance, tracking accuracy, hallucination rates, latency, and API cost.
• AI Security & Guardrails: Apply responsible‑AI controls including prompt‑injection mitigations, PII redaction, output filtering, rate limiting, audit logging, and access controls.
• Ecosystem Integrations: Connect AI services with security scanners, ticketing platforms, SIEMs, and monitoring stacks to deliver actionable, automated security workflows.
• Automation & MLOps: Automate data preparation, embedding refreshes, eval runs, and health checks using Python, Shell scripts, Git, Docker, and CI/CD pipelines.
• Cross‑Functional Collaboration: Partner with security, DevOps, infrastructure, and engineering teams to translate complex security requirements into scalable AI solutions.

Candidate Profile & Qualifications

Experience: 4–6 years of core software engineering and AI development experience.

Education: B.Tech or M.Tech in Computer Science, Information Technology, AI/ML, or a related field.

Core Technical Skills:

Python & Backend: Strong Python (FastAPI/Flask, async patterns, packaging, testing); working knowledge of Java for backend REST APIs.

LLM Frameworks & APIs: Hands‑on experience with LLM provider APIs (Anthropic, OpenAI, Azure OpenAI, Vertex AI) and frameworks (LangChain, LlamaIndex, LangGraph, or Haystack).

Vector Databases & RAG: Practical experience with vector stores (pgvector, Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, or Vertex AI Vector Search).

LLM Evals & Tooling: Experience building evaluation sets using frameworks like RAGAS, DeepEval, Promptfoo, or LangSmith.

Infrastructure & Web: Linux/Shell scripting, Docker, Git, CI/CD, basic HTML/CSS/JS, and experience with at least one major cloud platform (Azure, GCP, or AWS).

Certifications (Any one required):

CISSP, CCSP, AZ‑500, Azure AI Engineer Associate (AI‑102), AWS Certified Security – Specialty, or Google Professional Cloud Security Engineer.

(Desirable: CISM, CEH, OSCP, Google PMLE, AWS ML Specialty, CKA, Terraform Associate, or SC‑100).