Principal AI/GenAI Platform Architect
US client via staffing partner · Austin, TX | San Francisco, CA | Los Angeles, CA | Minneapolis, MN | Chicago, IL
- Location
- Austin, TX | San Francisco, CA | Los Angeles, CA | Minneapolis, MN | Chicago, IL · Onsite
- Salary band
- Band not stated
- Type
- Contract
- Level
- Principal
- Work authorization
- Sponsorship offered
Stack
Python · Java · Go · TypeScript · React · Azure OpenAI · Amazon Bedrock · Vertex AI · Kubernetes · CI/CD · Infrastructure as Code · LangChain · LangGraph · LiteLLM · OpenTelemetry · RAG · Vector Databases · MCP · Microservices · Distributed Systems
About the role
Role: Principal AI/GenAI Platform Architect Location: Austin, TX | San Francisco, CA | Los Angeles, CA | Minneapolis, MN | Chicago, IL (ONSITE) Duration: 24+ Months W2 Only... Work authorization: Any work authorization can apply for these openings. Education Requirement - Bachelor's Degree in: Computer Science, Information Technology, Or related field Level: Senior Technical Lead / Architect / Director-mapped Player-Coach Position Overview - We are seeking a Senior AI/GenAI Platform Architect / Technical Lead who started their career as a hands-on Software Engineer and has evolved into designing and leading enterprise AI/ML and Generative AI platforms. - This is not a pure Data Scientist, ML Researcher, AI Strategy, or management-only position. - The ideal candidate has a strong software engineering foundation in Python, Java, Go and/or TypeScript/React, distributed systems, APIs and cloud-native architecture, combined with recent hands-on experience building enterprise AI/GenAI platforms and agentic systems in production. - We are particularly interested in candidates who have built AI platforms or products from the ground up, rather than primarily supporting existing environments. - Experience working with Fortune 500 enterprises and complex or highly regulated environments is strongly preferred. A combination of large-enterprise and startup/product-building experience is especially valuable. What You'll Do - Own the architecture and technical direction of an enterprise AI/GenAI platform. - Define the reference architecture for the AI control plane, shared platform services, SDKs, templates and developer experience. - Architect and build model gateways supporting multiple AI providers such as Azure OpenAI, Amazon Bedrock, Vertex AI and other LLM providers. - Implement model routing, failover, quotas, rate limiting, tenant isolation, key management, token accounting and cost allocation. - Design and build enterprise GenAI runtimes supporting LLM applications, RAG, context and memory management, vector/hybrid search and tool execution. - Architect agentic AI platforms, including agent, model, prompt and tool registries, versioning, lineage, approvals and promotion processes. - Implement MCP-style tool interoperability and secure integration between AI agents and enterprise systems. - Build AI observability and traceability covering prompts, model calls, tool calls and agent execution. - Establish evaluation frameworks for AI quality, hallucination/accuracy, drift, latency, reliability and cost. - Implement enterprise AI security and guardrails, including PII/PHI protection, prompt-injection defenses, identity, least-privilege access and policy enforcement. - Establish platform engineering practices using Kubernetes, infrastructure as code, CI/CD, secrets management, secure SDLC and cloud-native architectures. - Define production SLOs, capacity and reliability standards and participate in incident management. - Remain hands-on with production code, architecture reviews, prototypes and critical technical components. - Make pragmatic build-vs-buy decisions and evaluate AI platform technologies and vendors. - Partner with Product, AI Engineering, Data Science, Security and enterprise application teams. - Initially operate as a player-coach and help build and lead a platform engineering team of approximately 3–8 engineers. Required Experience - - 10–15+ years of experience across software engineering, platform engineering, distributed systems, cloud architecture or related engineering disciplines. - Strong early-career and continuing foundation as a hands-on Software Engineer. - Significant recent experience architecting or building enterprise AI, GenAI or agentic AI platforms in production. - Strong hands-on development experience with Python plus at least one of Java, Go or TypeScript. - Strong understanding of APIs, microservices, distributed systems, testing, code reviews and secure software development. - Hands-on understanding of LLMs, model gateways, RAG, vector databases/search, embeddings, agents, prompts, tool calling and AI evaluation. - Experience with AI observability, tracing, governance and guardrails. - Strong cloud experience with Azure, AWS and/or GCP. - Experience with Kubernetes, containers, CI/CD and infrastructure as code. - Experience designing highly available, secure and scalable production platforms. - Demonstrated ability to make architecture decisions and communicate with senior technical and business stakeholders. - Ability to remain technically hands-on while providing leadership to engineering teams. Strongly Preferred Azure OpenAI, Amazon Bedrock and/or Vertex AI LiteLLM or comparable model-gateway architecture LangChain, LangGraph or comparable agent frameworks MCP / enterprise AI tool integration Vector and hybrid search technologies OpenTelemetry Langfuse, Arize or comparable AI observability/evaluation platforms Enterprise identity and secrets-management technologies Experience protecting PII/PHI or other sensitive enterprise data Experience in healthcare or another highly regulated industry Fortune 500 enterprise experience Combination of enterprise + startup/product-building experience
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