AI Platform Engineer — Agentic SDLC

Company Description

Artificial Intelligence. Automation. Cloud Engineering. Advanced Analytics.
For Enterprises, these are key factors of success. For us, they're our core expertise.

We work with global iconic brands. We bring them a unique value proposition through market-leading technologies and business process excellence. At the heart of it all is Digital Engineering - the foundation that powers rapid innovation and scalable business transformation.

We've created 363 unique and independent inventions, 250 of which are AI-based and rolled up under several patent grants in critical technologies. Leveraging our advanced products and platforms, we drive digital transformation at scale, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless "as-a-service" model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. With proven strategies and agile execution, we don't just enable change - we engineer digital outcomes.
Sutherland
Digital Outcomes.

Job Description

• Extend and harden an AI-driven software development lifecycle platform built on Kiro IDE. The platform uses autonomous agents, MCP tool integrations (Rally, Playwright, Git, Confluence), steering files, and event-driven hooks to orchestrate requirements gathering, architecture design, code generation, test automation, and deployment gating — all AI-first.

  build new agent capabilities, design RAG pipelines for context-aware code generation, create governance guardrails, and integrate with enterprise ALM/DevOps tools. This is not a testing role or a DevOps role — it's building the platform that makes all SDLC phases AI-native.

Key Areas of Responsibilities:

• Design and build AI agents that orchestrate multi-step SDLC workflows (fetch → generate → execute → validate → sync)
• Build RAG pipelines that feed architecture docs, coding standards, and Rally artifacts as grounded context to LLMs
• Implement MCP servers and tool integrations (Rally, Playwright, Git, Confluence, Azure DevOps)
• Author steering files (persona, governance, lifecycle) that constrain agent behavior with formal rules
• Build self-healing and auto-remediation systems with bounded autonomy and human escalation
• Design state machines for artifact lifecycles (requirements → design → code → test → deploy)
• Create event-driven hooks for CI/CD integration, nightly runs, and release gating
• Implement property-based testing to formally verify system correctness
• Package and deploy agent infrastructure (Docker, pipelines, credential management)

Qualifications

Skills Required:

Core Language

TypeScript / Node.js

AI/LLM

Azure OpenAI (GPT-4), prompt engineering, structured outputs

Agent Framework

Kiro IDE agents, MCP (Model Context Protocol), tool-use patterns

RAG / Context

Embedding pipelines, vector search, document chunking, context grounding

Testing

Playwright, fast-check (PBT), Jest

ALM Integration

Rally, Azure DevOps, Jira (bidirectional sync)

DevOps

GitHub Actions / Azure DevOps Pipelines, Docker, AKS

Frontend

React 18, TailwindCSS, shadcn/ui (for dashboards/reporting)

Backend

Express, Prisma, PostgreSQL, Redis/Bull queues

Documentation

Markdown-first, Word export, Mermaid diagrams

Must-Have Skills

• AI Agent Systems — Built or extended multi-step autonomous agents with tool-use, guardrails, and human-in-the-loop patterns
• RAG Pipelines — Designed retrieval-augmented generation systems (embedding, chunking, vector DB, context injection)
• TypeScript / Node.js — Production-grade, 4+ years
• LLM Integration — Azure OpenAI or equivalent; prompt engineering, structured outputs, function calling
• Full-Stack Architecture — Can design end-to-end systems (API, queue, DB, frontend, infra)
• CI/CD & DevOps — Pipeline authoring, Docker, scheduled automation, release gates

State Machine / Workflow Design — Lifecycle management, valid-transition enforcement, event-driven orchestration

Nice-to-Have

• MCP (Model Context Protocol) experience or similar tool-use protocols
• Playwright test automation
• Rally / Azure DevOps API integration
• Property-based testing (fast-check, QuickCheck)
• Salesforce application
• Experience with Kiro, Cursor, Windsurf, or similar AI-native IDEs
• Formal verification or correctness-by-construction approaches

Additional Information

Backfill position for Nayeem Mohammed (Emp ID:700971) in GE digital under Manish Purwar