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FDE Agentic SDLC Principal Developer

Hexaware · India

Mixed hiring record · median 27 days open

100100

Hiring signal

Actively hiring

Posted today · still listed on the employer's own board · How we score

All reasons
  • 29% of this employer's openings are over 60 days old

In its favour

  • Posted today
  • Still listed on the employer's own board

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FDE Agentic SDLC Principal Developer at Hexaware. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Job Description Role

FDE Agentic SDLC Principal Developer Role Summary

Exp 16 yrs + Strong in at least one of Java / .NET / Python / JavaScript-TypeScript; Git, CI/CD, test automation, containers and worked on public Cloud platform Work fluently inside an agentic coding tool (Claude Code, Copilot, Cursor): task decomposition, iterative steering, and knowing when to restart a loop Repo and spec grounding, retrieval over enterprise context, prompt and instruction file design Build verification harnesses so output is provably correct, not plausibly correct Own the client’s AI-SDLC transformation and its economics.

Define the target operating model

pod archetypes, role mix, control points, pilot-to-portfolio ramp

Own unit economics

token and infrastructure cost modeling, cost per story/release, build-vs-buy, self-hosted vs. API LLM TCO Set the client’s model portfolio strategy: frontier vs. open-weight vs.fine-tuned SLM, multi-vendor and exit risk, roadmap and deprecation planning, sovereign and on-prem constraints

Shape the commercial construct

outcome-based and productivity-linked pricing, gainshare, and the delivery risk behind it

Set platform and reference architecture

tool standardization, MCP/context platform, eval and observability layer, model governance

Establish AI governance with CISO/legal/compliance

policy, IP, model risk, approval workflow, audit posture Advise CIO/VP Engineering as a peer; lead adoption and change across engineering leadership Diagnose stalled adoption at the system level, not the tooling level

Feed field learning back into the offering

assets, accelerators, playbooks, capability building Mentor Band 2–3 FDEs and build the bench

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