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Retrieval Augmented Generation Jobs in Minnesota

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

This role requires strong expertise in Generative AI, RAG (Retrieval-Augmented Generation), and enterprise integrations. The ideal candidate should be capable of independently delivering scalable AI ...

Data & Software Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

... retrieval-augmented generation, or scripted helpers for teammates). • Experience working with marketing, analytics and customer data • Experience contributing to data/table architecture • ...

... Retrieval augmented generation (RAG) • Structured data semantics • Reusable prompt and skill • Demonstrate measurable impact on research productivity, decision velocity, and analytical depth ...

Senior Data Architect

Oslo, MN

$68.75 - $91.75/hr

Own the architecture for AI-augmented data workflows -- retrieval-augmented generation, semantic and vector search, and agentic pipelines -- that make the platform's data genuinely useful to ...

Build and architect AI-driven systems - Design and lead the implementation of enterprise-scale AI systems, including multi-component pipelines, retrieval-augmented generation (RAG) architectures, and ...

Showing results 21-40

Retrieval Augmented Generation information

What does a retrieval augmented generation engineer do?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a retrieval augmented generation?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What skills and qualifications are needed for retrieval augmented generation?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Minnesota? The most popular types of Retrieval Augmented Generation jobs in Minnesota are:
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Infographic showing various Retrieval Augmented Generation job openings in Minnesota as of August 2026, with employment types broken down into 67% Full Time, 31% Part Time, and 2% Contract. Highlights an 69% Physical, 2% Hybrid, and 29% Remote job distribution.

Director, AI Engineering & Agentic Platform

FAVARH

Minneota, MN • Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Job description

Together we fight for everyone's opportunity for a better financial future.

We will do this together - with customers, partners and colleagues. We will fight for others, not against: We will stand up for and champion everyone's access to opportunities. The status quo is not good enough ... we believe every individual and every community deserves access to financial opportunities. We are determined to support both individuals and communities in reaching a better financial future. We know that reaching this future depends on our actions today.

Like our Purpose Statement, Voya believes in being bold and committed to action. We are committed to a work environment where the differences that we are born with - and those we acquire throughout our lives - are understood, valued and intentionally pursued. We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work. Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision.

Are you ready to join a company with a strong purpose and a winning culture? Start your Voyage - Apply Now

Role Overview

At Voya Investment Management, we are committed to building innovative, responsible, and scalable technology solutions that enable better investment outcomes for our clients. Our vision for AI is grounded in delivering secure, governed, and high-impact capabilitiesthat augment investment decision-making, improve operational efficiency, and enhance client engagement.

Get to Know the Opportunity

As a Director, AI Engineering & AgenticPlatform, you will be responsible for designing, building, and operating the AI engineering capabilities. This role is a builder-operator hybrid, focused on delivering production-grade AI systems - not research prototypes - that can be trusted and scaled across investment research, distribution, and operational functions.

You will lead the development of shared AI platform services, including LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows, enabling multiple data science and engineering teams to deliver use cases faster, with stronger governance and reliability.

This role requires a combination of deep technical expertise in LLMOps and AI system architecture, platform thinking, and strong leadership in enterprise environments, particularly within the context of financial services where security, compliance, and trust are critical.

The Contributions You'll Make

AI Platform Architecture & Engineering

  • Design and implement scalable AI architectures, including:

    • LLM-powered applications

    • Retrieval-Augmented Generation (RAG) systems

    • agentic / multi-step workflows

    • vector search and retrieval services

    • model serving and inference layers

  • Establish reusable platform services, APIs, and design patterns to accelerate delivery across multiple teams.

  • Define reference architectures and engineering standards for production AI systems.

LLMOps / MLOps Enablement

  • Build and operationalize AI delivery pipelines:

    • CI/CD for models, prompts, and workflows

    • prompt versioning and lifecycle management

    • evaluation and testing frameworks

    • model and artifact registries

  • Implement monitoring for:

    • response quality and hallucination control

    • latency, throughput, and system reliability

    • cost observability and optimization

  • Establish scalable experimentation and evaluation frameworks to measure AI performance and reliability.

Responsible AI, Governance, and Security

  • Design AI systems with strong controls for:

    • data security and privacy

    • auditability and traceability

    • entitlements and access controls

    • data lineage and governance

  • Partner with risk, compliance, and security teams to embed Responsible AI practicesinto development and deployment processes.

  • Ensure alignment with regulatory expectations and model risk management standards.

Engineering Execution & Operational Excellence

  • Lead delivery of production-grade AI systems with a focus on:

    • scalability and reliability

    • latency and performance optimization

    • operational readiness and support

  • Evaluate and integrate third-party AI platforms and tools where appropriate.

  • Drive cost-effective architecture and FinOps practices for AI workloads.

Data Platform Integration

  • Partner closely with data engineering and platform teams to integrate AI capabilities with:

    • Snowflake and Databricks environments

    • structured and unstructured data pipelines

    • APIs and enterprise data services

    • semantic and knowledge-layer architectures

  • Enable seamless access to governed datasets for AI applications.

Leadership & Stakeholder Management

  • Serve as a technical leader and advisor to senior stakeholders across business and technology teams.

  • Translate business needs into scalable AI platform capabilities and solutions.

  • Lead and mentor a team of AI / ML engineers and technical leads.

  • Drive adoption of AI capabilities through enablement, best practices, and reusable frameworks.

Minimum Knowledge and Experience

  • Bachelor's degree in Computer Science, Engineering, or related field.

  • 10+ years of experience in software engineering, ML engineering, or platform engineering.

  • 3+ years in a leadership role driving complex engineering initiatives or leading teams.

AI Engineering & Architecture

  • Hands-on experience designing and deploying:

    • LLM-based applications

    • RAG systems

    • agentic AI workflows

    • vector databases / semantic search solutions

  • Strong understanding of prompt engineering patterns and evaluation methodologies.

  • Experience with model serving, inference optimization, and production deployment.

ML Engineering / Platform Mindset

  • Strong background in building scalable, production-grade systems with focus on:

    • reliability and observability

    • latency and performance

    • cost optimization

  • Experience developing shared platforms or reusable services across multiple teams.

LLMOps / MLOps

  • Experience implementing:

    • CI/CD pipelines for ML / AI systems

    • model and artifact registries

    • evaluation and regression pipelines

    • monitoring and alerting frameworks

  • Familiarity with prompt lifecycle management and AI system governance controls.

Data Platform & Cloud Technologies

  • Strong experience with modern data / AI platforms, including:

    • Databricks and/or Snowflake

    • APIs and microservices architectures

    • unstructured data processing pipelines

    • semantic layer or knowledge graph concepts

Enterprise & Financial Services Context

  • Experience working in regulated environments with strong requirements for:

    • security and data privacy

    • governance and auditability

    • SDLC and change management processes

  • Financial services or investment management experience strongly preferred.

Soft Skills

  • Excellent communication and stakeholder management skills.

  • Ability to influence technical and non-technical audiences.

  • Strong problem-solving and strategic thinking capabilities.

Nice to Have

  • Experience with Azure AI services, Copilot Studio, or similar enterprise AI tools.

  • Familiarity with investment management workflows (research, portfolio construction, risk, distribution).

  • Experience building internal AI developer platforms or enablement frameworks.

  • Knowledge of FinOps practices for AI and data platforms.

  • Exposure to knowledge graphs, semantic layers, or enterprise search platforms.

#LI-LW1

Compensation Pay Disclosure:

Voya is committed to pay that's fair and equitable, which means comparable pay for comparable roles and responsibilities.

The below annual base salary range reflects the expected hiring range(s) for this position in the location(s) listed. In addition to base salary, Voya offers incentive opportunities (i.e., annual cash incentives, sales incentives, and/or long-term incentives) based on the role to reward the achievement of annual performance objectives. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Voya Financial is willing to pay at the time of this posting.

Actual compensation offered may vary from the posted salary range based upon the candidate's geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

$180,000-$190,000

Be Well. Stay Well.

Voya provides the resources that can make a difference in your lives. To us, this means thriving physically, financially, socially and emotionally. Voya benefits are designed to help you do just that. That's why we offer an array of plans, programs, tools and resources with one goal in mind: To help you and your family be well and stay well.

What We Offer

  • Health, dental, vision and life insurance plans
  • 401(k) Savings plan - with generous company matching contributions (up to 6%)
  • Voya Retirement Plan - employer paid cash balance retirement plan (4%)
  • Tuition reimbursement up to $5,250/year
  • Paid time off - including 20 days paid time off, nine paid company holidays and a flexible Diversity Celebration Day.
  • Paid volunteer time - 40 hours per calendar year

Learn more about Voya benefits (download PDF)

Critical Skills

At Voya, we have identified the following critical skills which are key to success in our culture:

  • Customer Focused: Passionate drive to delight our customers and offer unique solutions that deliver on their expectations.
  • Critical Thinking: Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution.
  • Team Mentality: Partnering effectively to drive our culture and execute on our common goals.
  • Business Acumen: Appreciation and understanding of the financial services industry in order to make sound business decisions.
  • Learning Agility: Openness to new ways of thinking and acquiring new skills to retain a competitive advantage.

Learn more about Critical Skills

Equal Employment Opportunity

Voya Financial is an equal-opportunity employer. Voya Financial provides equal opportunity to qualified individuals regardless of race, color, sex, national origin, citizenship status, religion, age, disability, veteran status, creed, marital status, sexual orientation, gender identity, genetic information, or any other status protected by state or local law.

Reasonable Accommodations

Voya is committed to the inclusion of all qualified individuals. As part of this commitment, Voya will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please reference resources for applicants with disabilities.

Misuse of Voya's name in fraud schemes