Remote Prompt Engineer Jobs in Chicago, IL (NOW HIRING)

ThePrincipal AI Engineeris a senior individual contributor responsible for translating enterprise AI strategy into scalable, secure, and production-ready solutions. This role serves as the connective tissue between strategy and execution-owning solution architecture, technical standards, anddelivery ofAI-enabled products across the organization.

Working side by side with Product, Design, Engineering, Security, and Platform teams, you deliver AI-driven solutions that delight customers and accelerate time to value-while balancing feasibility, scalability, cost, and compliance. You set architectural direction and remain deeply hands-on, ensuring the organization applies AI responsibly and effectively toreal businessproblems.

You guide how and when to apply AI capabilities-copilots, agents, and vendor integrations-while enforcing architectural guardrails and elevating engineering maturity. You translate vision into architecture, patterns, and working software that deliversmeasurable outcomes. You are equally comfortable influencing executives and diving into code to unblock delivery.

Our engineering team is built on the principles of humans over code. We are a tight-knit group of lifelong learners in a constant quest to be a team that is greater than the sum of its parts. Come join us!

KeyResponsibilities

• Set the technical vision for how the organization builds with AI-architecting agents, agentic systems, and GenAI-powered products that redefine what our platform and customers can do.

• Own end-to-end solution architecture for AI and AI-enabled products (discoverytodesign todeployment), ensuring security, reliability, cost efficiency, and maintainability across cloud and on-prem environments.

• Drive experimentation and rapid prototyping at the frontier of applied AI-multi-agent orchestration, emerging model capabilities, and novel tooling-then convert the most promising experiments into production-grade systems.

• Identify, evaluate, and scale high-impact AI use cases (e.g., MCP, agentic workflows,retrievaland reasoning systems) that unlock new product capabilities and multiply engineering productivity.

• Serve as a hands-on architecture authority for GenAI and applied AI solutions, designing systems and ensuring alignment with enterprise standards set by the AI Center of Excellence.

• Establish and evolve reference architectures and reusable patterns for GenAI and applied AI (RAG, agents/orchestration, vector search, prompt & tool design, event-driven microservices, API gateways).

• Select fit-for-purpose models and services (e.g., Azure OpenAI, Bedrock, Vertex, OSS LLMs, embedding models), articulating clear tradeoffs across performance, latency, privacy, and cost.

• Partner with product and platform teams to ship production-grade solutions, driving work from prototype pilot scaled production.

• Define and implement best practices for CI/CD, Infrastructure as Code, andMLOps/LLMOps, including model versioning, prompt/config management, evaluation frameworks, drift detection, and safety monitoring.

• Ensure observability and operational readiness (tracing, guardrails, red-teaming, cost dashboards, SLOs, runbooks) before production cutover.

• Set the technical bar through design reviews, threat modeling, critical pull request reviews, coding standards, and documentation discipline.

• Evangelize effective use of copilots, agent frameworks, andintegrationSDKs to improve developer velocity without compromising quality or security.

• Lead architecture discovery with business stakeholders: frame problems, quantify constraints, and translate business goals into technical roadmaps.

• Define and track outcome-based KPIs (time to first value, cost to serve, task success, accuracy, CSAT/NPS, deflection).

• Communicate architectural tradeoffs, risks, and roadmaps in clear, executive-ready language.

• Publish andmaintainarchitecture decision records (ADRs) and platform documentation to ensure transparency and alignment.

Education & Experience

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or equivalent practical experience.

• 10+ years in software engineering, solution architecture, or platform engineering, including 3-5+ years delivering applied ML/GenAI solutions in production.

• Demonstrated experience leading architecture across multiple teams or products, not just contributing as an individual architect.

• Extensivehandsonexperience with cloud platforms (GCP preferred), including:

• Vertex AI,BigQuery, Dataflow, Pub/Sub

• Cloudnativemicroservices, APIs, event streaming

• Containers and orchestration (Kubernetes/GKE)

• Infrastructure as Code (Terraform)

• Deep practicalexpertisewith GenAI patterns: RAG, vector databases, prompt engineering & evaluation, agent design, function/tool calling, and orchestration.

• Strong command ofMLOps/LLMOps, including CI/CD for models and prompts, offline/online evaluation, telemetry, drift detection, and safety monitoring.

Skills & Abilities

• Experienceoperatingin regulated industries (financial services, healthcare, public sector) or similarlyhightrustenvironments.

• Strong background in security, privacy, andcompliancebydesign, including OAuth/OIDC, secrets management, data protection, and AI safety controls.

• Proven ability to influence without authority, aligning product, engineering, security, and business stakeholders.

• Exceptional written and verbal communication skills, withdemonstratedexecutive presence.

• Certifications (nice to have): Cloud Architect, Security (e.g., CISSP/CCSK), or equivalent.

Other Requirements:

• Ability to work occasional overtime.

• Occasional travel (up to ~15%).

• Occasionalafterhourswork to support releases or incidentresponses.

• Prolonged periods of sitting at a desk and working on a computer.