Associate Principal AI Engineer

Request Technology — United States · Posted ~3 hours ago

Lead Full-time Hybrid No Visa

Skills

AI engineering agentic AI AI application development data engineering software/application engineering infrastructure engineering data pipelines cloud computing AI AWS cloud infrastructure

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Summary ✨ AI‑Generated

An experienced AI engineer is sought for a hybrid role building and deploying agentic AI applications in a highly regulated enterprise environment. The position spans architecture through production and offers the opportunity to shape an expanding AI engineering function, with depth expected in data, application, or infrastructure engineering.

Highlights

Bonus-eligible hybrid leadership opportunity focused on building agentic AI capabilities, shaping an emerging AI engineering function, and working across data, application, and infrastructure engineering.

Description

Associate Principal, AI Engineering *We are unable to sponsor for this permanent Full-time role* *Position is bonus eligible* Location: Chicago, IL Work Arrangement: Hybrid (3 days on site) We are seeking an Associate Principal, AI Engineering to help build and evolve next-generation agentic AI capabilities within a highly regulated enterprise environment. This is an opportunity for an experienced engineer who is interested in AI and wants to help shape a growing AI engineering function. You don't need to be an expert across every area — we're looking for depth in at least one of three areas: Data Engineering, Software/Application Engineering, or Infrastructure Engineering, along with strong communication and collaboration skills. What You'll Do Design, build, and deploy AI-powered applications and agentic workflows from architecture through production.Help develop the data and technology foundation that makes enterprise information consumable by AI models.Build data pipelines and ETL/ELT processes across enterprise sources such as ServiceNow, Jira, and SaaS applications.Design agent orchestration, tool integrations, context management, and evaluation workflows.Build and support AWS infrastructure for AI applications and services.Develop scalable, production-ready solutions using modern engineering practices, APIs, containers, and CI/CD.Implement safeguards for AI-specific risks including prompt injection, hallucinations, data privacy, and output validation.Build audit logging and human-in-the-loop controls for AI workflows operating in a regulated environment.Partner with business and technical stakeholders to translate complex requirements into practical solutions.Mentor early-career engineers through technical guidance, code reviews, and architecture reviews.Help establish engineering standards and best practices for a rapidly evolving AI organization. Three Engineering Paths You don't need to be equally strong in all three. We're looking for deep expertise in at least one: Data Engineering — Highest Current Priority ETL/ELT and enterprise data pipelinesData modeling and data integrationBuilding a "knowledge substrate" that makes enterprise data accessible to AIExperience with data from platforms such as ServiceNow, Jira, and SaaS applicationsSoftware / Application Engineering Python and API developmentLLM-powered applications and agentic workflowsDistributed systems and application architectureAgent orchestration and tool/context integrationInfrastructure Engineering AWS cloud infrastructureInfrastructure as Code and automationDocker/containerizationCI/CD and deployment pipelinesKubernetes is a plus What We're Looking For 4–7+ years of software/data/infrastructure engineering experience with ownership of production systems.Strong Python and proficient SQL.Experience building LLM-powered applications, AI solutions, or agentic systems — deep AI experience is not required.Strong fundamentals in APIs, distributed systems, cloud infrastructure, or data engineering.Experience with AWS and modern engineering practices.Familiarity with Docker, CI/CD, and containerization.Interest in emerging AI technologies and a willingness to learn quickly.Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders.Experience mentoring or supporting the development of other engineers. Preferred Experience Anthropic Claude / Anthropic API or OpenAI experience.Agent orchestration or Model Context Protocol (MCP) integrations.Kubernetes and Terraform.Production AI/LLM applications operating at scale.AI security, red-teaming, prompt-injection defense, or adversarial testing.Data engineering, data pipelines, or data modeling.Financial services or other highly regulated industry experience.Master's degree in Computer Science, Engineering, or a related technical field. Why This Role? You'll have the opportunity to help build enterprise-grade agentic AI from the ground up, working with technologies such as Anthropic Claude and AWS while helping establish the engineering practices, data foundation, and infrastructure needed to scale AI across the organization. This is a hands-on technical leadership opportunity where AI interest, engineering fundamentals, communication, and the ability to mentor others are just as important as having years of specialized AI experience. This position is not eligible for employment visa sponsorship. Candidates must be legally authorized to work in the United States without the need for sponsorship now or in the future.