Applied AI Engineer, Security

SP Software; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

SP Software is seeking a Senior Principal Engineer (Applied AI) to design and implement AI-native security workflows. The role focuses on production-grade engineering, with validated designs and end-to-end delivery.

You will monitor, instrument, and document systems so the operations team can manage them, while addressing production defects at root cause. The position requires experience in agentic frameworks, REST/GraphQL APIs, and a strong background in Python with TS/JS or Go.

Qualifications

• 5+ years in software engineering with ownership of production systems.
• Built and shipped agentic systems into production, not prototypes.
• Strong Python and at least one of TypeScript/JavaScript/Go with code quality practices.

Responsibilities

• Build AI-native capabilities for security workflows.
• Deliver production-grade engineering with tested, instrumented systems.
• Collaborate with multiple teams and extend solutions per approved designs.
• Address defects in production to root cause and resolve quickly.

Skills

Python

TypeScript/JavaScript

Go

Production systems

Testing & maintenance

REST & GraphQL APIs

Observability

CI/CD pipelines

Documentation

Education

Bachelor's or Master’s in Computer Science

Equivalent practical experience

Tools

REST

GraphQL

OAuth

Containerization

CI/CD

Job description

WE ARE HIRING FOR THE ONE OF MNC CLIENT,

PAYROLL: SP SOFTWARE PVT LTD

NOTICE PERIOD:IMMEDIATE TO 15 DAYS

LOCATION:BANGLORE

INTERVIEW MODE : F2F(27TH AND 29 OCT)

Work Location and Address: Dell 10(5days WFO)

Role & responsibilities

Job Description:- Applied AI Engineer, Security

Senior Principal Engineer (I9) | Individual Contributor | Security Resiliency Organization

Position Summary

We are seeking a Senior Principal Engineer to build the AI-native capabilities that replace how security work is performed today.

Security processes today run across multiple functional teams, frequently duplicated with different tooling and different definitions of done. This role re-engineers and implements the rationalized version of those processes as AI-native workflows, working from an approved solution design and directly with the teams whose work is being agentified.

The expectation is production-grade engineering. Systems are delivered tested, instrumented so that the agent operations team can monitor them, and documented sufficiently for another engineer to extend them. Defects found in production are resolved by this role at root cause.

Required Skills and Qualifications

• 12+ years in software engineering with direct ownership of systems in production


• Agentic systems you personally built and shipped into production, not prototypes, notebooks, or proofs of concept


• Strong programming proficiency in Python and at least one of TypeScript/JavaScript, Go, or an equivalent language, with demonstrable code quality practice covering testing, review, refactoring, and maintainability


• Hands‑on implementation experience across:


• Agent loops and tool calling: loop control, sub-agent delegation, state management and checkpointing, and idempotent handling of consequential actions


• Context engineering: retrieval and search, memory, grounding in enterprise data, prompt assembly, and structured or schema‑constrained output


• Testing and validation: automated tests for behavior that varies between runs, regression suites, and validation against defined acceptance criteria


• Cost and latency engineering: token accounting, prompt and response caching, model routing with fallback, and context compaction


• Process re‑engineering experience: analyzing an existing workflow and rebuilding it around what automation makes possible, rather than encoding current practice into software


• Experience replacing an existing manual or fragmented business process with software, working directly with the people who perform that process today


• Integration engineering: REST and GraphQL APIs, event‑driven consumers, OAuth and scoped credential handling, schema and contract versioning, and resilient behavior under partial failure


• Observability and delivery engineering: structured logging, distributed tracing, and metrics for systems whose behavior varies between runs, plus CI/CD pipelines, automated quality gates, and containerized deployment


• Ability to work independently from written specification, deliver against committed timelines, and communicate progress and blockers without prompting


• Bachelors or masters degree in computer science or a related field, or equivalent practical experience

Preferred Skills and Qualifications

• Experience applying AI within a security domain such as application security, DevSecOps, vulnerability management, code analysis, or software supply-chain security


• Experience building MCP servers or agent tooling, or extending AI coding assistants such as Claude Code, GitHub Copilot, or Cursor


• Working knowledge of agentic frameworks and orchestration libraries, and judgment about when to use them


• Experience with LLMOps in production, covering versioning, staged rollout, and regression detection


• Familiarity with the OWASP Top 10 for LLM Applications and with secure development practice


• Experience ramping quickly onto an unfamiliar codebase and becoming productive in it

MANDATORY Technical Skills: AT LEAST 5+YRS IN Python, LangGraph, Lang Fuse, LLM must haves Typescript/JavaScript. Hands on Production based Implementation experience is mandate.

Bachelors or masters degree in computer science or a related field, or equivalent practical experience