Principal Full Stack AI Engineer

Vertex is seeking a Full-Stack AI Engineer to help build, extend, and operate our Agentic AI platform end to end. In this role you will develop AI agents and the services, APIs, and interfaces around them, and connect the platform to the systems, tools, and data sources that make AI valuable in real enterprise workflows. 

The ideal candidate is a versatile engineer who is comfortable across the stack including backend services and APIs, agent frameworks and orchestration, data and retrieval pipelines, and lightweight front-end experiences with real depth in enterprise integration design, MCP/A2A protocols, event-driven architectures, and authentication patterns. This individual will play a key role in ensuring AI capabilities are embedded into day-to-day work at Vertex and not as isolated proofs of concept, but as production-ready solutions integrated into the enterprise ecosystem. 
 

Key Responsibilities 

• Platform and integrations: connecting the agentic AI platform to enterprise systems, third-party tools, and business-critical services through MCP, A2A, APIs, webhooks, and event-driven patterns 

• Agent and service development: building agents, tools, and the backend services that support tool use, orchestration, memory, and action execution 

• Data and retrieval: making structured and unstructured enterprise content usable by AI workflows through ingestion, retrieval, and grounding patterns 

• User-facing experiences: building and extending lightweight interfaces, chat surfaces, and developer-facing SDKs and connectors that put agents in the flow of work 

• Reliability and governance: observability, evaluation, security reviews, and the standards that keep agentic solutions safe and supportable in a regulated environment 

• Build and ship AI and agentic capabilities end to end—from backend services and APIs to the interfaces and connectors users and developers interact with 

• Design, build, and maintain integrations between the AI/agentic platform and enterprise systems, internal applications, third-party tools, and business services 

• Implement secure, scalable connectivity patterns that enable AI agents and workflows to access data, trigger actions, and interact with enterprise platforms 

• Develop and support integrations using MCP, A2A, APIs, webhooks, and event-driven architectures 

• Create reusable connectors, SDKs, middleware components, and service patterns that accelerate onboarding of new tools and systems into the AI platform 

• Implement agent capabilities such as tool use, orchestration, retrieval, and action execution, and tune them for accuracy, latency, and cost 

• Partner with platform, product, data, security, and enterprise application teams to ensure solutions meet technical, business, and compliance requirements 

• Design robust authentication and authorization patterns for AI services, including identity propagation, token handling, and access control 

• Enable AI workflows to interact reliably with core enterprise platforms such as collaboration tools, knowledge systems, workflow tools, and line-of-business applications 

• Build data and retrieval pipelines that make structured and unstructured sources usable by AI and agentic applications 

• Implement monitoring, logging, tracing, evaluation, error handling, and alerting across agents and integration services 

• Ensure solutions are resilient, maintainable, observable, and aligned with enterprise architecture standards 

• Contribute to platform governance by defining standards, documentation, onboarding guidance, and best practices 

• Troubleshoot and resolve issues related to connectivity, data exchange, authentication, latency, and downstream service dependencies 

• Evaluate emerging standards and tools in AI engineering, system interoperability, and enterprise integration to inform platform evolution 

Required Qualifications 

• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related technical field; equivalent practical experience may be considered 

• Experience in software engineering, AI/application engineering, or platform engineering, including shipping production services 

• Full-stack development experience in Python and/or TypeScript, spanning backend services and APIs plus modern front-end or developer-facing surfaces 

• Hands-on experience building with LLMs and agent frameworks, including tool calling, orchestration, retrieval-augmented generation, prompting, and evaluation 

• Strong hands-on experience designing and implementing API-based integrations in enterprise environments 

• Experience with MCP, A2A, service-to-service communication, or similar integration/interoperability patterns 

• Strong understanding of event-driven architecture, messaging systems, asynchronous processing, and workflow-based integration design 

• Experience with authentication and authorization standards such as OAuth, OIDC, SSO, service principals, secrets management, and token-based security 

• Familiarity with enterprise application integration patterns, middleware, and distributed systems design 

• Experience building secure, scalable, and reliable production services on modern cloud platforms 

• Strong problem-solving skills and ability to work across multiple systems, teams, and technical domains 

• Strong written and verbal communication skills with the ability to document and explain technical approaches clearly 

• Understanding of AI-native software engineering practices, including effective and responsible use of AI coding assistants and software engineering agents 

Technical Skills 

• Python and/or TypeScript across backend and front-end 

• LLM APIs, agent frameworks, tool calling, and orchestration 

• Prompt design, evaluation harnesses, and quality/cost/latency tuning 

• Retrieval-augmented generation, embeddings, and vector stores 

• MCP and A2A protocols 

• REST APIs and service integration 

• Webhooks and event-driven integration patterns 

• Enterprise application integration 

• Authentication and authorization design 

• OAuth, OIDC, SSO, and token management 

• Distributed systems and microservices 

• Messaging and asynchronous processing 

• Observability, logging, tracing, and monitoring 

• Data exchange patterns across enterprise systems 

• Secure connectivity and secrets management 

• Cloud platforms and cloud-native architectures 

• Error handling, resiliency, and performance optimization 

• Versioning, testing, CI/CD, and deployment of production services 

Preferred Skills 

• Experience building or integrating AI and agentic platforms with enterprise tools and business systems 

• Experience with Microsoft AI and cloud technologies such as Azure AI Foundry, M365 Copilot, and agent frameworks 

• Familiarity with workflow orchestration platforms and automation frameworks 

• Experience building reusable connectors or SDKs for platform extensibility 

• Knowledge of enterprise data platforms, document systems, knowledge repositories, and collaboration tools 

• Experience with regulated environments such as biotechnology, pharmaceuticals, healthcare, or life sciences 

• Experience supporting platform governance, security reviews, and technical documentation 

• Understanding of observability and evaluation practices for complex, multi-system agentic workflows