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Retrieval Augmented Generation Rag Jobs in Chicago, IL

Develop end-to-end solutions leveraging modern AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), APIs, orchestration frameworks, and AI-assisted automation.

Develop end-to-end solutions leveraging modern AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), APIs, orchestration frameworks, and AI-assisted automation.

Retrieval-Augmented Generation (RAG) architectures * AI agents and orchestration frameworks * Develops intelligent copilots and assistants using Copilot Studio, integrating enterprise data and ...

Implement agent architectures including tool use, multi-step workflows, and retrieval-augmented generation (RAG) patterns * Integrate AI agents with enterprise systems, APIs, and data sources

Software Engineer - Product

Chicago, IL · On-site +1

$120K - $140K/yr

OVERVIEW We're seeking a passionate Software Engineer to join our Experimental Engineering team focused on enhancing and developing our AskCR Retrieval-Augmented Generation (RAG) application. This ...

AI Full Stack Engineer

Chicago, IL · Remote

$70 - $75/hr

AWS Solutions Architect, AWS Developer, or Kubernetes Application Developer. - Hands-on experience with Langchain/LlamaIndex and RAG (retrieval-augmented generation) architecture. - Proven experience ...

Apply Early

Deep knowledge of Retrieval-Augmented Generation (RAG) , vector databases (Pinecone, Milvus, Weaviate, ChromaDB, FAISS), and AI agents. * Strong programming skills in Python and experience with API ...

New

Sr. AI/ML Engineer

Deerfield, IL · On-site

$106K - $145K/yr

Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise systems * Understanding of Agentic AI architectures (e.g., LangChain, CrewAI, AutoGPT) for orchestrated ...

Sr AI Engineer

Chicago, IL · On-site

$107K - $147K/yr

... Retrieval-Augmented Generation (RAG) applications using tools like Azure AI Search, vector databases, and secure enterprise connectors to deliver contextual insights. • Build and deploy agents ...

AI Consultant

Downers Grove, IL · On-site

$70K - $110K/yr

Working understanding of AI and machine learning concepts, including large language models (LLMs), retrieval-augmented generation (RAG), workflow automation, data pipelines, and system integrations

Apply Early

AI Consultant

Downers Grove, IL · On-site

$70K - $110K/yr

Working understanding of AI and machine learning concepts, including large language models (LLMs), retrieval-augmented generation (RAG), workflow automation, data pipelines, and system integrations

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How much do retrieval augmented generation rag jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for retrieval augmented generation rag in Chicago, IL is $20.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $21.78 per hour, depending on experience, location, and employer.
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Innovation AI Developer

Kirkland & Ellis LLP.

Chicago, IL • On-site

Full-time

Medical, Retirement, PTO

Posted 19 days ago


Job description

About Kirkland & Ellis
At Kirkland & Ellis, we don't just meet the standard for legal excellence - we set it. Our culture is built on teamwork, ingenuity and an unwavering commitment to continuous growth. We tackle the most sophisticated legal challenges with bold ideas and innovative solutions, powered by the exceptional experience and ambition of our 7,000+ people, including 4,000+ attorneys, across 24 offices worldwide. Our dedicated professionals share our lawyers' commitment to excellence and show up each day to do meaningful work that helps drive global business, investment and innovation forward.
What You'll Do
Are you energized by building enterprise-grade AI solutions that solve complex, high-impact challenges in a sophisticated professional services environment? As an Innovation AI Developer at Kirkland & Ellis, you will play a pivotal role on our Innovation Engineering team-designing and deploying intelligent, secure, and scalable AI applications that transform how we deliver legal services and operate our business.
In this role, you'll partner closely with attorneys, business leaders, data scientists, and infrastructure teams to translate nuanced legal and operational challenges into practical AI solutions with measurable outcomes. From early-stage use case discovery through production deployment and monitoring, you'll work across the full AI lifecycle-leveraging large language models (LLMs), retrieval-augmented generation (RAG), classical machine learning, and modern cloud architectures to drive efficiency, quality, and informed decision-making.
This is an opportunity to shape enterprise-grade AI capabilities at one of the world's leading law firms, working at the intersection of advanced engineering and high-impact legal work.
• AI Solution Architecture & Development - Collaborate with legal and business stakeholders to identify high-value AI use cases, define measurable success criteria (e.g., efficiency, quality, risk reduction), and architect scalable solutions using Python and modern AI frameworks such as OpenAI, Azure OpenAI, Hugging Face, LangChain, and LangFlow.
• Retrieval-Augmented Generation (RAG) & Intelligent Systems - Design, build, and maintain RAG pipelines using vector databases and knowledge graph solutions. Develop AI agents that automate multi-step workflows and enable sophisticated task orchestration.
• Reusable Engineering & Scalable Innovation - Create reusable libraries, patterns, and documentation that support long-term innovation and maintainability across the firm's AI ecosystem.
• Evaluation & Model Governance - Design and maintain LLM evaluation frameworks to measure accuracy, robustness, safety, and alignment to use-case objectives. Ensure AI systems meet firm security, privacy, and governance standards.
• Production Deployment & Infrastructure Enablement - Support continuous integration and continuous delivery (CI/CD) workflows, containerization (Docker), and orchestration (Kubernetes) to ensure production readiness. Partner with infrastructure and security teams to support hybrid cloud and on-premise deployments in sensitive data environments.
• Stakeholder Partnership & AI Enablement - Serve as a subject matter resource for attorneys and business teams, advising on prompt engineering, model selection, and architecture decisions. Support pilot implementations, user training, and feedback loops to drive adoption and measurable impact.
• Emerging Technology & Strategy Contribution - Evaluate new tools, open-source libraries, and vendor platforms to inform firm AI strategy. Contribute to internal education and thought leadership on AI best practices.
What You'll Bring
• Education - Bachelor's degree in computer science or a related field preferred.
• Experience - 7+ years of experience in professional services, legal, or technical environments, with demonstrated hands-on experience building and deploying AI applications.
• AI Engineering Expertise - Strong Python development skills and experience designing and implementing RAG pipelines, working with vector databases (e.g., Pinecone), and building AI agents and multi-service AI architectures-particularly within Azure environments.
• Cloud & DevOps Proficiency - Familiarity with Azure services (e.g., Cognitive Search, Cosmos DB, AI Studio), as well as Docker, Kubernetes, and CI/CD practices that support scalable, production-ready deployments.
• Evaluation & Data Integration - Experience designing and maintaining LLM evaluation frameworks (e.g., Promptfoo, OpenAI Evals, LangSmith) and integrating structured and unstructured data sources into AI systems.
• Security & Governance Awareness - Experience operating within environments that require strict adherence to security, privacy, and governance standards for sensitive data.
• Business Acumen & Communication - Proven ability to conduct stakeholder discovery, quantify return on investment (ROI), and translate ambiguous challenges into clearly defined AI requirements. Strong communication skills with the ability to explain complex technical concepts to non-technical audiences.
• Legal Domain Exposure (Preferred) - Experience supporting legal use cases such as due diligence, contract review, or legal research, and prior law firm experience.
If you're motivated to design intelligent systems that elevate how legal services are delivered-while shaping the future of AI within a high-performing, collaborative environment-we'd love to hear from you.
Compensation
The base salary range below represents the low and high end of the salary range for this position in Chicago, New York. This range may differ based on your geographic location and cost of living considerations. At Kirkland & Ellis, we consider compensation more than just a base salary. We offer an exceptional range of flexible benefits including comprehensive healthcare, paid time off, and retirement. We also offer personal support and tailored learning and development opportunities all designed to help you realize your full potential both in life and at work.
Compensation Range:
Chicago: $177,000 - $197,000
New York: $177,000 - $218,000
How to Apply
Thank you for your interest in Kirkland & Ellis LLP. To complete an application and submit your resume, please click "Apply Now."
Don't meet every job requirement? That's okay! If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others at Kirkland.
Equal Employment Opportunity
All employment decisions, including the recruiting, hiring, placement, training availability, promotion, compensation, evaluation, disciplinary actions, and termination of employment (if necessary) are made without regard to the employee's race, color, creed, religion, sex, pregnancy or childbirth, personal appearance, family responsibilities, sexual orientation or preference, gender identity, political affiliation, source of income, place of residence, national or ethnic origin, ancestry, age, marital status, military veteran status, unfavorable discharge from military service, physical or mental disability, or on any other basis prohibited by applicable law. #LI-Hybrid #LI-LC1