Applied AI Engineer

Skills

About the Role

You will partner with enterprise customers to take AI systems from opportunity selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation harnesses and integrations, resolve technical blockers, guide decisions on reliability and safety, and create reusable deployment tooling and guidance.

Requirements

• Track record designing, building, and delivering AI or machine-learning systems in enterprise environments
• Experience taking systems from prototype to production
• Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering
• Python proficiency
• Knowledge of AI application stacks
• Knowledge of AI system evaluation using representative data, graders, production signals, and human judgment
• Experience with enterprise integrations, reliability, observability, security, privacy, data governance, performance, and cost
• Ability to connect technical decisions to customer workflows, adoption, and business outcomes

Responsibilities

• Identify high-value customer opportunities and translate them into architectures, implementation plans, evaluation strategies, and success criteria
• Design, build, and deploy AI systems for customer problems
• Build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators
• Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance
• Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve blockers
• Help customers move prototypes into reliable production systems and sustained adoption
• Translate deployment experience into product feedback
• Create reusable architectures, tooling, playbooks, and technical guidance

Benefits

• Relocation assistance for new employees