AI engineer
AI EngineerLocation: Phoenix, AZ (Onsite) FulltimeMust Have Technical/Functional Skills10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructureAI engineers with recent NodeJS/Javascript/Typescript experienceProven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.Fluency with AI-assisted and agentic development workflows.Comfort operating in ambiguous problem spaces and translating them into shipped, reliable autonomous systems.Ability to influence technical direction and align teams without formal authority.Experience in workflow engines, async processing, queues, and streaming systems.Languages: NodeJS/Javascript/Typescript, Python, GoAPIs and services: REST, gRPCCloud and infrastructure: AWS and/or GCP, KubernetesDistributed systems: event-driven architectures, including KafkaOrchestration Frameworks: LangGraph, LangChain, AirFlow, etcIntegration of commercial and open-source LLMs into agentic workflowsAgent and orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitivesModel-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to TensorFlowStrong schema, validation, and state management practices using tools such as Pydantic (Python) and Zod (TypeScript)Experience building agentic systems in fintech or other regulated industries.Experience as a founding engineer or early technical leader in AI-driven products.Demonstrated success delivering technically complex autonomous systems that customers actively rely on.Meaningful contributions to open-source AI or agentic frameworks.Familiarity with fine-tuning, model optimization and inference pipelines is a plus.Roles & ResponsibilitiesDrive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.Design, build, and operate production-grade agentic AI systems used across multiple products.Own and evolve shared agentic AI capabilities, including:Agent frameworks and orchestration layersPlanning, tool use, and memory strategiesRetrieval and grounding (RAG) pipelinesLLM infrastructure, inference, and model gatewaysEvaluation, observability, and safety tooling for autonomous systemsLead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.Mentor senior engineers and raise the technical bar for agentic AI development through example and influence.