Role Overview

Your mission is to supercharge developer velocity by abstracting away the complexities of AI infrastructure, model evaluation, and LLM orchestration, turning cutting-edge AI capabilities into seamless internal tools.

Key ResponsibilitiesPlatform & AI Integration Infrastructure

- Design and maintain secure internal API gateways and proxies to manage, route, and optimize the consumption of third-party foundation models (e.g., Anthropic, OpenAI).
- Architect and optimize context delivery infrastructure , leveraging vector databases and data pipelines to index internal codebases, wikis, and technical documentation so developer AI tools can provide highly accurate, company-specific answers.
- Implement local caching layers and request-routing strategies to minimize latency and eliminate duplicate external API calls across the engineering organization.

Developer Productivity & Workflow Automation

- Lead the rollout and configuration of enterprise AI-assisted coding tools and IDE extensions, abstracting away authentication and setup hurdles to ensure a frictionless developer experience.
- Integrate AI capabilities directly into CI/CD pipelines , building automated workflows for initial pull request reviews, boilerplate generation, unit test creation, and initial code-quality checks.
- Continuously optimize the internal development lifecycle by identifying friction points where customized AI agents or developer bots can accelerate shipping times.

Security, Governance & Cost Management

- Partner deeply with Security and Data Governance teams to build robust data-masking and filtering layers that prevent proprietary code, intellectual property, or PII from being sent to external models.
- Establish strict cost-governance guardrails , creating centralized telemetry, token quotas, and budget alerting to monitor and manage third-party AI vendor spend.
- Implement comprehensive observability and logging to track API uptime,



usage trends, and latency across different engineering teams.

Technical Enablement

- Act as the primary internal champion for AI adoption , successfully onboarding and mentoring an engineering team transitioning from zero AI usage to highly proficient, AI-assisted development.
- Create documentation, host workshops, and establish best practices around effective prompt engineering, security guardrails, and maximizing the utility of internal AI tools.

Qualifications & SkillsCore Platform & Technical Experience

- 5+ years of experience in Platform Engineering, Developer Experience (DX), or Internal Tools engineering.
- Proven background building secure API gateways or proxies , specifically focusing on data filtering, request routing, and traffic management.
- Strong infrastructure foundation , with deep familiarity managing containerized environments, cloud-native infrastructure, and automated CI/CD workflows.
- Proficiency in Python or Go to write custom internal backend services, CLI tools, and developer plugins.

AI & Developer Tooling Ecosystem

- Solid understanding of the AI developer tool landscape , including foundation model APIs, IDE extensions, and context-injection techniques.
- Experience implementing data privacy guardrails , such as automated sensitive data masking, token filtering, and secret detection within software development lifecycles.
- Familiarity with backend data engineering concepts , specifically vector databases and data pipelining to support internal retrieval-augmented generation (RAG) systems.

Enablement & Collaboration Skills

- Developer-centric empathy : A strong commitment to understanding engineering friction points and building tools that genuinely improve the daily developer experience.
- An enablement mindset : The patience, clarity, and communication skills required to successfully coach and transition an engineering team from zero AI usage to confident power users.

Work Location: Remote

📌 Senior Platform Engineer, Ai Developer Experience (India)
🏢 XTRM
📍 India