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Remote Retrieval Augmented Generation Jobs (NOW HIRING)

Global Alliant Inc

AI Engineer

Rockville, MD · Remote

$140K/yr

Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible to obtain and maintain ... Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG)

Global Alliant Inc

AI Engineer

Rockville, MD · Remote

Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible to obtain and maintain ... Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG)

SumerSports LLC

AI Application Engineer

Strong understanding of prompt engineering, retrieval-augmented generation, and evaluation ... Remote working environment * A flexible, unlimited time off policy * Generous paid holiday schedule ...

Morningstar

Senior Software Engineer

Chicago, IL · On-site +1

$153K/yr

Remote work requests will be considered consistent with company's remote work policy. Job ... Multiprovider integration (OpenAI, Anthropic, MistralAI, etc.), Retrieval augmented generation ...

Jahnel Group

Senior AI Engineer

Schenectady, NY · On-site +1

$120K - $160K/yr

Apply prompt engineering and retrieval-augmented generation (RAG) techniques to improve model ... Schenectady, New York * 100% Remote for the right candidate Compensation Package (Salary ...

Mastech Digital

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 ...

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Remote Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as a Remote Retrieval Augmented Generation Engineer, and why are they important?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are some common challenges faced by professionals working in Remote Retrieval Augmented Generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is Remote Retrieval Augmented Generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.
More about Remote Retrieval Augmented Generation jobs
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What are the most commonly searched types of Retrieval Augmented Generation jobs? The most popular types of Retrieval Augmented Generation jobs are:
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Remote Retrieval Augmented Generation jobs near you
Infographic showing various Remote Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% Remote job distribution.

AVP, AI (Data Science/Engineer) Remote - EST

Archgroup

Hartford, CT • Remote

$185K - $235K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago

Job description

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility.

Strategic Analytics is a dynamic and growing team at Arch that drives innovation and transforms how the businessoperates. We build AI-first, agent-driven products that change how Arch underwrites, services, and learns from its book - combining frontier LLMs, multi-agent orchestration (MCP, A2A), retrieval-augmented generation, evaluation harnesses, and traditional ML.Our missionis broad: agentic automation, decision support, AI-driven insights, and the platform engineeringrequiredto make all ofitproduction-grade.

We have a strongtrack recordof success(productionalizingdozens ofhigh qualityGen AI products over the last 3 years) -weaim to continue scaling these efforts and are seeking an AVP AIEngineering tolead thearchitecture & developmentof true multi-agent systems within Strategic Analytics. Reporting to theSVP of AI & Automation, you will design andoperateorchestrations where agents communicate directly with one another - not just sequential, hand-off-driven workflows.After architecting themultiagentsystem,you willautomate complex decisions by usingData Science frameworks/processes.This will happen in thesystemyoucreateandproductionsolutionsmust workathighlevelsof accuracy.You willpartnerwithImplementation Engineering (IE)on theorchestrationentry points and any infrastructure-side connectors.

Key Responsibilities

  • Designourmulti-agent orchestration patterns (master-orchestrator + specialized worker agents) using protocols such as MCP and A2A.

  • This may be a blend of build & buy

  • Lead end-to-end delivery of agentic underwriting and claims automations, from prototype throughtoproduction.

  • Use precision/recall, calibration, confidence thresholds, error analysis, and business-impact measurement todeterminewhen automation is safe to deploy

  • Design decision frameworks that combine LLMs, retrieval, traditional ML, business rules, and human review."

  • Identifythe conditions where the automation should be trusted, reviewed, or discarded

  • Partner with IE on orchestration entry-point design (e.g., Azure Function endpoints, master-agent gateways) so the AE/IE seam is clean and scalable.

  • Leadoffshore engineers and team members on agentic patterns, prompt engineering, and reliability practices.

  • Establish coding, evaluation, and observability standards for agentic systems within the AI & Automation Center of Excellence.

  • Translate business intent into working agentic systems - not just systems that compile, but systems that deliver measurable business outcomes.

Required Skills / Experience

  • 7+ years of software engineering and/or automation engineering experience.

  • 3+ years of Data science experience

  • 3+ years of people leadership experience

  • Demonstratedexperience buildingproduction grademulti-agent or agentic systems (beyondPOCwork).

  • Strongtrack recordofdeveloping supervised learning models (ML and/or GLMs)that have a financially measurable impact on the business

  • Strong experience sourcing & evaluating vendors

  • StrongPython experience

  • Resilient problem solving - comfortable with ambiguous problems and capable of breaking them into shippable increments.

  • Strong written and verbal communication; able tooperateacross IE, AE, DS, and business stakeholders.

  • Demonstrated, hands-on production experience (not POC-only) with the current AI stack: RAG, MCP / A2A or equivalent agent-to-agent protocols, agentic orchestration frameworks, and the ability to articulate where each is the right tool. Comfort scanning for and trialing new tooling as the space evolves.

Desired Skills / Experience

  • P&C insurance domain familiarity - underwriting, claims, or submission lifecycle.

  • Experience with retrieval-augmented generation (RAG),evaluationharnesses, and structured-output patterns.

  • Cloud experience in Azure (preferred for our stack) and/or AWS; familiaritywith private endpoints and enterprise-grade safeguards.

  • Experience leading multidisciplinary teams (onshore + offshore) for technology delivery.

  • Visibletrack recordof self-directed learning in the AI space - side projects, contributions to agentic frameworks, write-ups, conference talks, or other evidence that the candidate is investing personal time staying ahead of the curve.

Education

  • College degree in Computer Science, Software Engineering, Data Analytics, or equivalent practical experience.

#LI-LH1

#LI-REMOTE

For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

$185,000 - $235,000/year

  • Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

  • Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long-Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Click here to learn more on available benefits.

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you.If this job isn't the right fit but you're interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch's Talent Acquisition team.

10200 Arch Capital Services LLC

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