Principal (AI) Artificial Intelligence Engineer

NO SPONSORSHIP - NO OPTPrincipal , (AI) Artificial Intelligence EngineeringSALARY: $200K - $230k - $240k plus 30% bonusLOCATION: Chicago, ILHybrid 3 days onsiteLooking for an AI research and engineering expert. Python SQL data engineering AI LLM, LLM powered applicationsYou won't manage people; you'll do the work, set the technical standard, and lead through expertise. You'll be the primary driver of agentic AI capabilities, architecting and building the systems that connect AI agents to real enterprise workflows in one of the most consequential and carefully regulated environments in financial markets. Our team works directly with AWS and Anthropic, accessing Claude models through both.If you're a seasoned engineer who wants to stay hands-on, lead through technical excellence, and build agentic AI systems that matter this role was written for you.Define and execute AI technical roadmap, translating organizational priorities into concrete architectural decisionsLead agentic AI efforts: architect, build, and operate systems that connect AI agents to internal systems, data pipelines, and business workflowsLeverage direct relationships with AWS and Anthropic to evaluate and adopt new model capabilities and tooling as they become availableBuild and ship production AI applications on AWS using Claude and related Anthropic tooling, maintaining high standards for reliability, security, and auditabilityArchitect scalable systems that integrate LLMs and AI agents into internal systems, operational workflows, and business processes, owning decisions from design through production deploymentQualifications:Expert-level Python; proficient in SQLDeep system design expertise: distributed systems, microservices, event-driven architectures, APIs, and MCP serversHands-on experience with data engineering: pipelines, transformation, and data modelingAWS experience; comfort with Docker, Kubernetes, and CI/CD pipelinesStrong production AI/LLM experience, or demonstrated hands-on passion for the space with the engineering depth to ramp quicklyStrong working knowledge of AI risk vectors: hallucinations, prompt injection, bias, data privacy, and output validationBachelor's or Master's in Computer Science or a related technical field10+ years of software engineering and systems architecture experience, with demonstrated technical leadership5+ years as a senior individual contributor on complex, high-stakes production systems