AWS AI Platform Engineer
Raleigh, NC · On-site
Design and implement Retrieval-Augmented Generation (RAG) architectures * Build AI agents and multi-agent workflows for enterprise use cases * Design enterprise knowledge retrieval and semantic ...
AWS AI Platform Engineer
Raleigh, NC · On-site
Design and implement Retrieval-Augmented Generation (RAG) architectures * Build AI agents and multi-agent workflows for enterprise use cases * Design enterprise knowledge retrieval and semantic ...
... retrieval-augmented generation, and emerging AI applications. * Evaluate whether proposed AI use cases have sufficiently clear business purpose, accountable ownership, human oversight provisions ...
... retrieval-augmented generation, and emerging AI applications. * Evaluate whether proposed AI use cases have sufficiently clear business purpose, accountable ownership, human oversight provisions ...
Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and ...
Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and ...
Applied Responsible AI Lead
Raleigh, NC · On-site
... retrieval-augmented generation, and emerging AI applications. * Evaluate whether proposed AI use cases have sufficiently clear business purpose, accountable ownership, human oversight provisions ...
Applied Responsible AI Lead
Raleigh, NC · On-site
... retrieval-augmented generation, and emerging AI applications. * Evaluate whether proposed AI use cases have sufficiently clear business purpose, accountable ownership, human oversight provisions ...
LLM-powered document understanding and generation, Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy, Retrieval-augmented generation (RAG) pipelines ...
LLM-powered document understanding and generation, Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy, Retrieval-augmented generation (RAG) pipelines ...
Principal Data Scientist I
Raleigh, NC · On-site
$118K - $219K/yr
Advanced retrieval-augmented generation (hybrid search, ranking optimization), RAG * Embedding strategies and semantic search systems * Knowledge graph integration and graph-enhanced intelligence
Principal Data Scientist I
Raleigh, NC · On-site
$118K - $219K/yr
Advanced retrieval-augmented generation (hybrid search, ranking optimization), RAG * Embedding strategies and semantic search systems * Knowledge graph integration and graph-enhanced intelligence
Data Engineer
Cary, NC · On-site
$106K - $127K/yr
Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...
Data Engineer
Cary, NC · On-site
$106K - $127K/yr
Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...
Data Engineer
Cary, NC · On-site
$90K - $150K/yr
Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...
Data Engineer
Cary, NC · On-site
$90K - $150K/yr
Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...
... retrieval-augmented generation (RAG) enablement, and reusable templates) for safe and deliberate consumption across the organization. * Establish and champion DevSecOps practices for platform ...
... retrieval-augmented generation (RAG) enablement, and reusable templates) for safe and deliberate consumption across the organization. * Establish and champion DevSecOps practices for platform ...
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
AI Engineer/ML Engineer - Senior Developers - AI Training - Raleigh, US
Raleigh, NC · On-site +1
$80/hr
LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. * Technical Rigor: the ability ...
Quick apply
AI Engineer/ML Engineer - Senior Developers - AI Training - Raleigh, US
Raleigh, NC · On-site +1
$80/hr
LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. * Technical Rigor: the ability ...
LLM-powered document understanding and generation Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy Retrieval-augmented generation (RAG) pipelines Hybrid ...
LLM-powered document understanding and generation Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy Retrieval-augmented generation (RAG) pipelines Hybrid ...
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines * Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use ...
Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines * Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use ...
AI Lead
Raleigh, NC · On-site
Working knowledge of generative AI, large language models, copilots, agents, prompt/agent design, retrieval augmented generation (RAG), enterprise search, document intelligence, model evaluation, and ...
Quick apply
AI Lead
Raleigh, NC · On-site
Working knowledge of generative AI, large language models, copilots, agents, prompt/agent design, retrieval augmented generation (RAG), enterprise search, document intelligence, model evaluation, and ...
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Retrieval-augmented generation (RAG) pipelines * Hybrid ML + rules-based systems for structured content * Lead through execution and by example: * Actively writing code, not just delegating
Sr. Manager Of Data Science
$85 - $96/hr
LLM-powered document understanding and generation Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy Retrieval-augmented generation (RAG) pipelines Hybrid ...
Sr. Manager Of Data Science
$85 - $96/hr
LLM-powered document understanding and generation Agentic workflows balancing agent autonomy and efficiency with required structure and accuracy Retrieval-augmented generation (RAG) pipelines Hybrid ...
Senior Technical Marketing Engineer, AI
Raleigh, NC · On-site
$146K - $219K/yr
Direct experience with RAG (Retrieval-Augmented Generation), Vector Databases (such as Milvus or Pinecone), and infrastructure protocols including S3 object storage and high-performance networking.
Senior Technical Marketing Engineer, AI
Raleigh, NC · On-site
$146K - $219K/yr
Direct experience with RAG (Retrieval-Augmented Generation), Vector Databases (such as Milvus or Pinecone), and infrastructure protocols including S3 object storage and high-performance networking.
Senior Legal Counsel
Cary, NC · Hybrid
$129K - $175K/yr
... retrieval augmented generation ("RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements ...
Senior Legal Counsel
Cary, NC · Hybrid
$129K - $175K/yr
... retrieval augmented generation ("RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements ...
Retrieval Augmented Generation information
What are the typical daily responsibilities of a Retrieval Augmented Generation engineer?
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 job?
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 are the key skills and qualifications needed to thrive in the Retrieval Augmented Generation position, and why are they important?
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 Raleigh, NC? The most popular types of Retrieval Augmented Generation jobs in Raleigh, NC are:
What are popular job titles related to Retrieval Augmented Generation jobs in Raleigh, NC? For Retrieval Augmented Generation jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Raleigh, NC look for? The top searched job categories for Retrieval Augmented Generation jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Retrieval Augmented Generation jobs? Cities near Raleigh, NC with the most Retrieval Augmented Generation job openings:
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Job description
Job Role: AWS AI Platform Engineer
Location: Raleigh, NC/Pheonix, AZ
Job Description:
Must Have Technical/Functional Skills
Experience
- 10 15 years of experience in Cloud Engineering, Platform Engineering, or Enterprise Architecture
- 4+ years of experience designing and implementing AI/ML and Generative AI solutions
- 2+ years of hands-on experience building RAG systems and AI Agents
- Experience working in large enterprise or financial services environments is highly preferred
Role Summary
We are seeking a Senior Engineer AWS AI Platform & RAG Integration to serve as the technical bridge between the AWS Cloud Infrastructure team, Enterprise AI Platform team, Security, Networking, Data Engineering, and Application Development teams.
The Engineering Lead will drive the onboarding of AI use cases onto the enterprise AI platform by coordinating cloud infrastructure requirements, designing scalable AI integration patterns, and implementing Generative AI solutions using AWS native AI services.
This role combines technical leadership, solution architecture, hands-on engineering, and cross-functional coordination to accelerate enterprise AI adoption while ensuring scalability, security, governance, and operational excellence.
Key Responsibilities
AI Platform Integration
- Lead onboarding of business applications onto the enterprise AI platform
- Translate business and AI requirements into AWS infrastructure and platform capabilities
- Design reusable AI integration patterns and reference architectures
- Define enterprise standards for AI application integration
- Support multiple AI initiatives across business domains
RAG and Agentic AI Development
- Design and implement Retrieval-Augmented Generation (RAG) architectures
- Build AI agents and multi-agent workflows for enterprise use cases
- Design enterprise knowledge retrieval and semantic search solutions
- Develop reusable AI orchestration components and AI APIs
- Integrate enterprise data sources into AI knowledge bases
- Implement prompt engineering and context management strategies
AWS Cloud Platform Engineering
- Work with AWS Cloud Infrastructure teams to use AI to provision and configure AWS Cloud infrastructure
- Design cloud-native AI architectures using AWS managed services
- Support infrastructure automation and deployment pipelines
- Ensure high availability, scalability, and resilience of AI workloads
- Coordinate networking, IAM, security, storage, and compute requirements
Cross-Team Leadership
- Act as the primary technical liaison between:
o AWS Cloud Infrastructure teams
o AI Platform teams
o Security and IAM teams
o Networking teams
o Data Engineering teams
o Application Development teams
o Enterprise Architecture teams
- Lead technical workshops and architecture discussions
- Coordinate cross-functional delivery activities
- Mentor engineering teams adopting AI capabilities
AI Governance and Operational Excellence
- Ensure AI solutions comply with enterprise security and governance standards
- Design secure AI integration patterns
- Implement AI guardrails and Responsible AI controls
- Support AI evaluation, monitoring, and observability
- Drive AI platform best practices and reusable accelerators
Required Technical Skills
AWS Cloud: VPC, IAM, EC2, ECS, EKS, Lambda, S3, API Gateway, CloudWatch, CloudFormation, EventBridge, SNS/SQS, Step Functions, KMS, Secrets Manager, Terraform, Elasticsearch, Cost Analysis, Budgeting
AWS AI Services: Amazon Bedrock, SageMaker AI, Amazon Knowledge Bases, Amazon OpenSearch, Amazon Titan, Bedrock Agents, Bedrock Guardrails, Textract, Comprehend, Transcribe, Rekognition, Neptune
AI Technologies: RAG architecture, Vector databases, Embeddings, Vector Search, Sematic search, Prompt engineering, Context Engineering, Agentic AI, Multi-agent orchestration, MCP, LangChain, LangGraph, LlamaIndex, AI evaluation techniques, Hallucination Mitigation Techniques, AI governance, LLM Models (Anthropic)
Programming: Python, Java, REST APIs, SDK integration, Git, CI/CD, Claude Code
Data Skills: SQL, NoSQL, Document processing, Data chunking, Metadata management, Data ingestion pipelines
Leadership Skills: Executive communication, Cross-functional coordination, Technical leadership, Architecture governance, Stakeholder management
Preferred Qualifications
- Experience with enterprise AI platform implementation
- Experience in Banking or Financial Services
- Familiarity with Responsible AI and AI Governance frameworks
- Experience implementing secure AI solutions in regulated environments
- AWS Professional or Specialty Certifications
- Experience with DevSecOps and Platform Engineering practices