Applied AI Engineer, Security
Summary
Senior principal engineer, on SP Software payroll for an MNC client (Dell, Bengaluru, 5 days WFO), building production-grade AI-native workflows that re-engineer security processes: agent loops, tool calling, context engineering, cost/latency optimization, and observability using Python, TypeScript/JavaScript, LangGraph, LangFuse, and LLMs.
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
IF ANYONE INTRESTED PLEASE SHARE TO SAYINI.PRASANTHI@SPSOFTGLOBAL.COM
NOTE:ONLY SHORLISTED PROFILES WILL GET THE INTERVIEW CALLS.