Senior AI Engineer: End-to-End ML in Production

RWE Gruppe; Chicago (IL); On-site; USD 127,000 - 171,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) match

Education assistance

Parental leave

Paid time off

Job summary

RWE Americas, LLC in Illinois seeks a Senior AI Engineer I to own end-to-end AI capabilities within a product or across multiple products, from design to production. You will work on retrieval and context assembly, model logic, API integrations, and monitoring, with emphasis on trustworthy AI and responsible controls.

The role requires hands-on experience with Python, SQL, cloud platforms, containers, and CI/CD for AI projects, plus the ability to manage costs and latency in production, and

Qualifications

• Bachelor’s degree in CS, data science, or related STEM field.
• Minimum 5 years in software or AI/ML engineering roles with end-to-end ownership of AI/ML capabilities.
• Depth in two or three capability areas listed under Basic Function with familiarity across the rest.
• Production experience with Python and SQL, a major cloud platform, version control and code review, containerized deployment, and CI/CD for AI products and services.
• Hands-on experience with orchestration, agent, and retrieval frameworks.
• Practical experience developing ML models for supervised and unsupervised problems.
• Experience building and maintaining evaluation and regression testing for AI/ML systems.
• Working knowledge of AI-specific security and responsible AI controls.

Responsibilities

• Design, build, operate, and own end-to-end AI capabilities within a product or across multiple products, spanning retrieval and context assembly; model and agentic logic; integration with source systems and consuming applications (APIs, MCPs, authentication); monitoring and evaluation; and operational runbook maintenance
• Train and evaluate machine learning models for well-scoped problems such as classification, regression, anomaly detection, clustering, and forecasting, using operational and commercial data. Determine when and how to use ML models versus simpler statistical baselines
• Build retrieval and context pipelines against enterprise content using chunking, tagging, and a metadata strategy. Measure and report retrieval quality against a defined standard
• Design and maintain evaluation for these capabilities, including offline evals, automated scoring such as LLM-as-judge, and regression tests that run on every prompt or pipeline change to ensure quality before release. Monitor quality and drift signals in production
• Own inference cost and latency in production, tracking cost per transaction and end‑to‑end response time, and profiling where that time is spent. Make tradeoffs where needed to stay within agreed targets
• Implement human‑in‑the‑loop and AI‑specific security controls, including shadow and assisted modes, confidence and citation surfaces, override capture, audit trails, identity-scoped retrieval, input and output guardrails, tool permissions, and prompt injection resistance
• Take handover of application components built by technical delivery partners: read the code, close operational gaps, update the runbook, and maintain them in production
• Improve team efficiency by establishing reusable components and reference examples, reviewing code, and onboarding new engineers

Skills

Python

SQL

Cloud platform

Version control

CI/CD for AI

AI/ML engineering

Retrieval frameworks

Production monitoring

Security controls

Education

Bachelor’s degree in CS/DS

Tools

Docker

Kubernetes

Git

CI/CD tools

Job description

RWE Americas, LLC in Illinois seeks a Senior AI Engineer I to own end-to-end AI capabilities within a product or across multiple products, from design to production. You will work on retrieval and context assembly, model logic, API integrations, and monitoring, with emphasis on trustworthy AI and responsible controls.

The role requires hands-on experience with Python, SQL, cloud platforms, containers, and CI/CD for AI projects, plus the ability to manage costs and latency in production, and