Top Remote Artificial Intelligence Engineer Jobs in Chicago, IL

As a Senior AI Controls Solutions Engineer, you'll operationalize Phaidra's AI solutions for enterprise data center customers, collaborating with teams to model facilities and define product requirements, applying deep knowledge of control systems and AI technologies.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

As a Staff Software Engineer, you'll develop an AI-first platform, design cloud-native APIs, and collaborate on Site Builder experiences with a focus on scalability and quality code.

Design, develop, and maintain scalable CPQ solutions on Salesforce. Implement Apex and Lightning components, optimize existing systems, and mentor junior developers.

As a Staff AI Engineer, you will develop backend services, integrate APIs, and optimize existing systems within a complex AI platform environment, collaborating with cross-functional teams and ensuring high reliability and performance.

The Senior AI Engineer leads software implementation, mentors engineers, collaborates with product and DevOps teams, and ensures production reliability.

Design, build, and deploy enterprise-scale agentic and generative AI systems for healthcare. Architect multi-agent frameworks, implement advanced RAG and multimodal data pipelines, optimize LLM performance and latency, establish MLOps/CI-CD and secure containerized deployments, and collaborate with stakeholders to ensure clinical safety and compliance (HIPAA/HITRUST). Mentor developers and produce production-grade documentation.

Lead and deliver an enterprise AI platform and agent factory: design architecture, build cost-effective model infrastructure, harden security/SSO/IAM, enable developer adoption, and build agent workflows across the PDLC (ideation, development, deployment). Mentor engineers, steer delivery partners, and remain hands-on implementing agents, RAG pipelines, integrations, and observability to drive measurable productivity gains.

Embed with operational teams to identify and automate manual workflows using AI agents and code. Design, prototype, validate, and productionize agentic workflows with logging, monitoring, and guardrails. Collaborate with Product and Engineering, publish reusable automation modules, and iterate quickly based on user feedback.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

Unpaid AI engineering internship to design, build, and deploy ML solutions (NLP, computer vision, recommenders). Work on data preprocessing, model training/fine-tuning, containerized FastAPI microservices, and scalable deployments on Google Cloud Run. Contribute to code reviews, GitHub repos, and integration of third-party AI APIs.

As a Senior Agentic AI Engineer, you'll develop core systems for AI agents, focusing on reliability, observability, and production readiness, working hands-on with distributed systems and orchestration.

As a Senior AI Platform Engineer, you will design and build production software for AI Employees, manage technical delivery for client implementations, and ensure system reliability and performance.

The Senior AI Engineer will design and build core AI platforms, mentor engineers, and collaborate with various teams to deliver AI products for insurance workflows, ensuring compliance and operational efficiency.

Lead architecture and technical direction for a cloud-native, multi-tenant Student Journey Platform. Design and enforce standards for Kubernetes-based AI services (AKS), event streaming, ML model serving, autoscaling, observability, and compliance. Ensure scalable, reliable, cost-efficient infrastructure, resolve architectural risks and production issues, and align platform decisions with business growth and SLAs.

Fine-tune and align LLMs for specialized financial tasks; build agentic solutions with LangChain/Autogen; engineer ML pipelines for large financial datasets; deploy, monitor and scale production models; track AI research and integrate emerging tooling.

Design, build, and deploy AI-powered workflows, internal tools, assistants, and platform capabilities to automate operational processes. Integrate LLM APIs, RAG/vector retrieval, and backend systems, collaborate with product and operations, and deliver production-ready solutions that reduce manual work and scale GreenLight's operations.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

Act as the technical presales lead for AI agent and cloud identity security across North America: scope engagements, design and run POCs and architectures across AWS/Azure/GCP, secure non-human and machine identities, create repeatable technical assets, and partner with account teams to close deals.

Lead Conversational AI Developer responsible for developing chatbots and virtual assistants, integrating AI technologies, and improving user interactions through data analysis and software development.

Senior SRE on the IT Operations team owning reliability, monitoring, and incident response for AI infrastructure. Build automation, CI/CD and Kubernetes tooling, improve observability and documentation, and develop internal full-stack tools using Go or Python. Partner with Infrastructure, Security, and Compliance to scale secure, resilient AI deployment pipelines.

Own reliability, monitoring, and incident response for AI infrastructure; build automation and CI/CD tooling; manage Kubernetes/Docker production workloads; partner with infrastructure, security, and compliance; improve observability and documentation; develop internal full‑stack tooling in Go or Python.

The Senior AI Engineer will design and build autonomous AI agents for mental health applications, focusing on LLM integration and reinforcement learning techniques for user interactions.