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Salary
≈ $20k – $51k per year (Estimated)
Location
Hybrid (Pune, India)
Seniority
Principal · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Aug 12, 2026.

Overview
Company
Impact
Profile match
Perforce, a software company, offers a wide range of enterprise DevOps solution across the software development lifecycle.

Position Summary:

Perforce is looking for a Principal Software Engineer responsible for managing the backend architecture of our internal AI platform, Perforce Prism on our Enterprise AI team.

This role will own translating complex AI capabilities into developing scalable, production-grade solutions that drive real business impact. You'll work across technical teams and the business to embed AI into existing workflows and infrastructure, building solutions with measurable, lasting impact.

This role sits at the intersection of engineering and the business. If you thrive on taking emerging AI capability and making it work in practice, this is the role for you.

Responsibilities:

  • Own and operate the backend architecture of Perforce Prism, our internal AI platform. You are the technical owner of the platform's core infrastructure - including AI standard protocols and the AI services layer. You are accountable for reliability, observability, and performance in production, end to end. You'll partner closely with the teams owning MongoDB and ETL/orchestration infrastructure to ensure the platform's data and pipeline dependencies scale with it.
  • Lead the technical development strategy for Prism. Translate business and product requirements into scalable, secure AI platform designs. Establish patterns for AI pipelines, agent orchestration, and services that internal systems engineers and AI consumers can build on confidently - coordinating with adjacent infrastructure teams where the platform depends on their systems.
  • Continuously identify what's next. Stay ahead of the AI landscape. Proactively evaluate emerging models, frameworks, and tooling - and translate that into a prioritized roadmap of improvements that deliver real benefits: cost savings, efficiency gains, new capabilities.
  • Own AI efficiency and cost management for the Prism platform. Drive measurable improvements across inference cost, token usage, caching strategies, model selection, and prompt orchestration.
  • Govern AI responsibly. Implement AI governance frameworks and data stewardship practices aligned with SOX, SOC 2, PCI, PII, and data residency requirements. Partner with Security, Compliance, Legal, and Risk to ensure AI systems are trustworthy by design - not audited after the fact.
  • Work alongside AI support teams to raise technical capability across the group. Lead technical reviews, provide technical guidance, and help the team grow - without losing your own hands-on output.

Requirements:

  • 10+ years of enterprise software development experience
  • Experience working with agentic/AI software development workflows
  • Strong proficiency in JavaScript and TypeScript, including modern ES6+ syntax and static typing patterns
  • Hands-on experience building and running server-side applications with Node.js (e.g., REST APIs, async I/O, package management via npm/yarn)
  • Hands-on experience with LLM APIs, prompt engineering, custom skill development, and multi-turn orchestration
  • Production experience building and maintaining AI standard protocols - server design, tool registration, and context management
  • Experience with orchestration platforms
  • Strong MongoDB expertise, schema design, vector/embedding storage, and aggregation pipelines for AI knowledge retrieval
  • Working knowledge of enterprise compliance requirements: SOX, SOC 2 Type II, PCI-DSS, PII handling, and data residency
  • Hands-on experience applying AI to business use cases, beyond purely technical or engineering applications- Demonstrated ability to drive AI adoption through training, documentation, and enablement programs
  • A track record of delivering cost and efficiency improvements through inference optimization, caching, or model routing
  • Strong communication skills, able to present technical architecture to non-technical stakeholders and write clearly for both audiences
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