Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational ...
Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational ...
Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational ...
Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational ...
Familiarity with retrieval augmented generation (RAG) pipelines and how search quality feeds downstream LLM applications. * Background in information retrieval, natural language processing
Familiarity with retrieval augmented generation (RAG) pipelines and how search quality feeds downstream LLM applications. * Background in information retrieval, natural language processing
Senior ML Engineer
Lehi, UT · On-site
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Senior ML Engineer
Lehi, UT · On-site
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Senior ML Engineer
Lehi, UT · On-site
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Senior ML Engineer
Lehi, UT · On-site
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Senior ML Engineer
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Senior ML Engineer
$98K - $134K/yr
Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...
Nice to have: Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM library, HuggingFace library or ...
Nice to have: Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM library, HuggingFace library or ...
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
AI Engineer - Innovation Lab
Midvale, UT · On-site
Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.
Staff Cyber Security Engineer - AIDR/AISPM
Draper, UT · On-site +1
Strong knowledge of AI/ML concepts, behavioral analytics, large language models, retrieval-augmented generation, and AI agent architectures. * Experience evaluating, integrating, and operationalizing ...
Staff Cyber Security Engineer - AIDR/AISPM
Draper, UT · On-site +1
Strong knowledge of AI/ML concepts, behavioral analytics, large language models, retrieval-augmented generation, and AI agent architectures. * Experience evaluating, integrating, and operationalizing ...
Integrate AI and LLM capabilities, including OpenAI APIs, retrieval-augmented generation, conversational flows, and agent frameworks like LangGraph, along with GPT actions and MCP servers. * Stand up ...
Integrate AI and LLM capabilities, including OpenAI APIs, retrieval-augmented generation, conversational flows, and agent frameworks like LangGraph, along with GPT actions and MCP servers. * Stand up ...
Integrate AI and LLM capabilities, including OpenAI APIs, retrieval-augmented generation, conversational flows, and agent frameworks like LangGraph, along with GPT actions and MCP servers. * Stand up ...
Quick apply
Integrate AI and LLM capabilities, including OpenAI APIs, retrieval-augmented generation, conversational flows, and agent frameworks like LangGraph, along with GPT actions and MCP servers. * Stand up ...
Sr. Data Engineer
$107K - $128K/yr
Build and integrate AI-powered applications and agentic workflows (e.g., LLM-based agents, retrieval-augmented generation systems, workflow automation agents) * Design and implement data pipelines ...
Quick apply
Sr. Data Engineer
$107K - $128K/yr
Build and integrate AI-powered applications and agentic workflows (e.g., LLM-based agents, retrieval-augmented generation systems, workflow automation agents) * Design and implement data pipelines ...
Staff Cyber Security Engineer - AI Product Security
Draper, UT · On-site +1
$153K - $302K/yr
Strong knowledge of AI/ML concepts, behavioral analytics, large language models, retrieval-augmented generation, and AI agent architectures. * Experience evaluating, integrating, and operationalizing ...
Staff Cyber Security Engineer - AI Product Security
Draper, UT · On-site +1
$153K - $302K/yr
Strong knowledge of AI/ML concepts, behavioral analytics, large language models, retrieval-augmented generation, and AI agent architectures. * Experience evaluating, integrating, and operationalizing ...
Retrieval Augmented Generation Rag information
See Orem, UT salary details
$13.17 - $14.08
6% of jobs
$14.92 is the 25th percentile. Wages below this are outliers.
$14.08 - $14.99
20% of jobs
$14.99 - $15.90
13% of jobs
The median wage is $16.55 / hr.
$15.90 - $16.81
15% of jobs
$16.81 - $17.73
13% of jobs
$18.21 is the 75th percentile. Wages above this are outliers.
$17.73 - $18.64
15% of jobs
$18.64 - $19.55
3% of jobs
$19.55 - $20.46
2% of jobs
$20.46 - $21.37
4% of jobs
$21.37 - $22.29
7% of jobs
$22.29 - $23.20
1% of jobs
$13
$17
$23
How much do retrieval augmented generation rag jobs pay per hour?

Job description
Awardco is building a governed context system so that our people and, increasingly, our AI agents can trust the data they act on. As Principal AI Solutions Architect, you will own the technical design of that foundation: the hub-and-spoke master data model, the event-log flow into Snowflake, and the governed APIs that let AI agents access trusted data safely. Your first project is standing up a governed context system across Syncari, Snowflake, and Glean to deliver one trusted account and contact record and one certified definition behind our key metrics. Your broader mandate is to execute Phase 1 of our AI Operations plan, including a stateful multi-agent system that automates go-to-market workflows and helps close a significant pipeline gap. This is a hands-on, build-oriented role for an architect who is as comfortable designing survivorship rules across six systems as standing up production RAG and agent-to-agent workflows, and who will act as the technical anchor of a lean team and the architecture authority to our Software Advisory Board.
What you will do:
- Design the hub-and-spoke data schema that establishes Syncari as the overlay mastering operational records across Salesforce, HubSpot, and the other primary source systems without disrupting the existing Snowflake pipelines.
- Map and codify match and survivorship rules across the six primary systems, so conflicting records resolve into one trusted golden account and contact record with clear precedence logic and confidence thresholds.
- Architect the event-log flow into Snowflake, so operational state and change history stream reliably into certified, governed data structures using Snowflake Cortex.
- Define how AI agents access both datasets, operational (Syncari) and analytical (Snowflake), through governed APIs and MCP endpoints, enforcing read/write boundaries and human-approval gates.
- Design a stateful, multi-agent AI model and agent-to-agent (A2A) workflows, including the six micro-agents (identity, enrichment, qualification, routing, drafting, and feedback) that automate the manual middleware between HubSpot and Salesforce.
- Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational & process data for Glean and other downstream agents reason over certified truth instead of guessing.
- Architect semantic API to AI and Semantic Governance and version control so all company health metrics and processes such as ARR, Account Health, and SDR pipeline. Then, ensure it can be mapped to a trusted golden record to those definitions are unified for every team and tool shares one answer.
- Stand up stewardship queues and governed writeback, routing high-risk conflicts to named human owners and ensuring clean values flow back into source systems only after human approval.
- Partner with Data Engineers and Data Analysts to sequence and deliver the Phase 1 project roadmap, turning architecture into hands-on build work and instrumenting data-quality and KPI dashboards.
- Serve as the technical authority to the Software Advisory Board, documenting architecture decisions, presenting at the Month 3, 6, and 9 checkpoints, and providing the evidence base for the decision to scale to new data domains.
- 8+ years in data architecture, enterprise systems integration, or AI/ML solutions architecture, including hands-on design of master data management (MDM) or enterprise integration solutions.
- Hands-on experience with a enterprise service bus (ESB) or a modern MDM platform, such as Syncari, Reltio, Boomi, or MuleSoft, including schema design and match/survivorship rule configuration.
- Proven, hands-on experience building LLM applications on commercial APIs (OpenAI, Anthropic) and designing production retrieval-augmented generation (RAG) architectures.
- Demonstrated ability to design multi-agent or agent-to-agent AI systems, including stateful orchestration and governed tool/API access patterns.
- Strong working knowledge of a cloud data warehouse (Snowflake preferred), including event and log ingestion and API-based data access.
What will make you stand out:
- Direct experience with MindStudio, Syncari, Snowflake Cortex, Glean or similar platforms - or comparable MDM, semantic-layer, and AI search/orchestration platforms - in a governed-data setting.
- Understanding of Business Operational Systems systems (Salesforce, HubSpot, NetSuite) and customer or account data domains within a B2B SaaS company.
- Familiarity with the Model Context Protocol (MCP) or similar standards for governed AI agent access to enterprise data.
- Experience implementing data governance frameworks, including data contracts, stewardship workflows, and quality/KPI instrumentation.
- Awareness of AI regulatory and compliance requirements (for example, the EU AI Act) and experience building auditable, human-in-the-loop AI controls.
Why Awardco:
- We have a revolutionary, client-approved product.
- One of the fastest growing companies in the nation: 3x Inc. 500, 2x Deloitte Technology Fast 500, 2x Mountain West Capital Network Fast 100, 3x Fast 50 (Utah Business), and 3x UV50 Fastest Growing Companies (BusinessQ), to name just a few.
- Great Place to Work certified, ranked in Inc. Best Workplaces, one of the Best and Brightest companies to work for, and ranked on the Salt Lake Tribune's Top Workplaces.
- Backed by renowned investors, both local and national.
Awardco is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
Disclaimer: Please be aware that all official communication regarding your application will only come from an email address ending in @awardco.com. If you receive any communication from a different domain, it may be fraudulent, and we encourage you to report it.