> Markdown version of [/jobs/ext/1945704-director-ai-platform-engineering](https://www.wearedevelopers.com/jobs/ext/1945704-director-ai-platform-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, AI Platform Engineering - **Company:** SS&C Technologies, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $200,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Engineering, Code Review, Continuous Integration, Data Governance, Data Infrastructure, Distributed Systems, Python (Programming Language), Metadata Repositories, Open Source Technology, Azure Machine Learning, Software Engineering, Data Streaming, WebSocket, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Fastapi, Event Driven Architecture, AI Platforms, Kubernetes, Graphql, Data Management, Front End Software Development, Virtual Agents, Terraform, Docker, Microservices - **Published:** August 6, 2026 - **Apply:** https://wd1.myworkdaysite.com/recruiting/ssctech/SSCTechnologies/job/San-Francisco-CA/Director--AI-Platform-Engineering_R44905 ## About the Role * 10+ years in software engineering, with 5+ years in engineering leadership and management roles (managing managers or large teams) * Deep experience building and operating production platforms (API platforms, data platforms, or ML platforms) * Experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen) * Strong knowledge with Model Context Protocol (MCP) or similar tool-integration standards * Hands-on expertise with modern AI/ML ecosystem: LLM APIs (OpenAI, Anthropic, AWS Bedrock), agent frameworks, prompt engineering * Strong systems design: distributed systems, microservices, event-driven architecture * Production cloud native infrastructure at scale (Kubernetes, Docker, Terraform) * Python as primary backend language (FastAPI, async patterns) * Proven track record of shipping platform products used by multiple internal or external teams * Experience leading technical strategy at the organizational level (not just team-level), * Background in financial services or regulated industries (compliance, audit trails, data governance) * Experience with real-time streaming protocols (SSE, WebSocket, AG-UI) * Knowledge of data mesh / data platform architectures (GraphQL, dbt, data catalogs) * Exposure to Module Federation / micro-frontend architectures * Open source contributions or community leadership in AI/ML space * Experience scaling from 0*1 platform through growth stages ## Description * Define and execute the technical roadmap for the AI agent platform (multi-agent orchestration, LLM routing, tool integration, observability) * Architect for enterprise-grade multi-tenancy, security, and scalability * Drive platform standardization across agent frameworks (LangGraph, MCP protocol, AG-UI protocol) * Evaluate and integrate emerging AI technologies (new LLM providers, inference optimization, agentic frameworks) Team Leadership * Build, lead, and mentor a team of 8-15 platform engineers (backend, infrastructure, AI/ML) * Establish engineering best practices: code review, testing, CI/CD, documentation * Create a culture of technical excellence, ownership, continuous learning, prototyping and delivering * Foster cross-functional collaboration with product, data science, and business stakeholders Delivery & Operations * Own platform reliability, availability, and performance SLAs * Drive production readiness: observability, alerting, incident response, capacity planning * Deliver iterative platform capabilities through discovery-driven development processes * Manage dependencies across multiple consuming teams and agent developers Technical Decision Making * Lead architectural decisions using structured frameworks (DACI, ADR etc) * Evaluate build vs. buy vs. integrate trade-offs for platform components * Champion developer experience: APIs, SDKs, documentation, self-service tooling * Ensure AI agent platform security, compliance, and audit requirements ## Related Videos - [AI Won't Fix Your Engineering Culture](https://www.wearedevelopers.com/videos/100266-ai-won-t-fix-your-engineering-culture) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [AI-Augmented DevOps with Platform Engineering](https://www.wearedevelopers.com/videos/1614-ai-augmented-devops-with-platform-engineering) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)