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 current 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.

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 Experience Level Senior Level

📌 AI Platform Engineer - Software Development Lifecycle Automation (Bengaluru)
🏢 Sutherland Global Services Private
📍 Bengaluru