Overview:
In this role you will design, build and operate enterprise-ready AI agents that scale across cloud-native platforms. You work directly with clients as a technologist and trusted advisor to define use cases, prototype quickly, and deploy robust agentic workflows in complex environments. You will weave together disparate systems and ecosystems to enable real-world AI-native solutions. You’ll help shape patterns and playbooks for enterprise AI adoption, balancing performance, safety, and cost in multi-provider setups. Compensation / Benefits medical, dental, vision coverage life and long-term disability 401(k) plan bonus opportunities paid holidays paid time off
Responsibilities:
Design enterprise-ready AI agents including retrieval, orchestration, routing, tool invocation, evaluation harnesses, and observability Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) for seamless multi-provider pipelines Build cloud-native architectures using Kubernetes, Docker, microservices, serverless, CI/CD, and observability Tailor agentic applications across verticals (finance, healthcare, retail) to address domain-specific processes Lead client design workshops, POCs, and code-with sessions to shape data-driven agent workflows Define metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost Create reusable patterns, documentation, and best practices to influence client roadmaps Travel as needed to meet business requirements
Key requirements:
3+ years in cloud-native systems (APIs, microservices, containerization, serverless) 1+ year designing and deploying agentic solutions in production 2+ years with AI platforms (OpenAI, Claude, Vertex AI) and multi-provider pipelines 5+ years programming in Python, Java, or equivalent 5+ years deploying to production with CI/CD, IaC (Terraform, Helm), monitoring, and debugging 5+ years experience in client communication and leading workshops in ambiguity Bachelor's degree or equivalent work experience (minimum 12 years) leadership in workshops ability to operate in ambiguity strong client engagement and collaboration agent architectures and orchestration RAG and context engineering evaluation tooling