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Ai Rag Jobs in Austin, TX (NOW HIRING)

Principal AI Architect

Austin, TX · On-site

$120 - $150/hr

... RAG) Agent frameworks, Data pipelines, and Inference optimization. * Evaluate and integrate ... Agentic AI & Advanced Systems Provide architectural direction for Agentic AI systems, including:

New

Has built LLM harnesses/scaffolds with agentic loops, RAG pipelines, and tool-calling architectures ... AI platform/developer tooling, evaluation & observability frameworks, AI security & guardrails ...

AI Solutions Architect

Austin, TX · On-site +1

$62.50 - $82.25/hr

AI Solutions Architect Type: Contract / Consulting Duration: 6 months (extendable) Location: Remote ... RAG architecture together with the data and ML teams -- chunking strategies, hybrid retrieval ...

AI Agent Engineer Designs and develops AI-driven agentic solutions, including autonomous workflows and Retrieval-Augmented Generation (RAG) systems, to enhance productivity, automate processes, and ...

AI Solutions Architect

Austin, TX · Remote

$64.50 - $85/hr

AI Solutions Architect Type: Contract / Consulting Duration: 6 months (extendable) Location: Remote ... RAG architecture together with the data and ML teams -- chunking strategies, hybrid retrieval ...

Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data ... Define AI/ML technical capabilities, including: Generative AI systems Data pipelines Model ...

Principal AI Architect

Austin, TX · On-site

$150 - $180/hr

Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data ... Define AI/ML technical capabilities, including: Generative AI systems Data pipelines Model ...

Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data ... Define AI/ML technical capabilities, including: Generative AI systems Data pipelines Model ...

RAG and code/knowledge-graph design; retrieval-pipeline design and tuning. Production LLM systems ... Spec-driven development; power user of AI coding agents (Claude Code, Cursor, Codex). Outstanding ...

Principal AI Architect

Austin, TX · On-site

$150 - $180/hr

Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data ... Agentic AI & Advanced Systems*** Provide architectural direction for **Agentic AI systems ...

Showing results 21-40

Ai Rag information

See Austin, TX salary details

$31.7K

$57.7K

$82.8K

How much do ai rag jobs pay per year?

As of Aug 8, 2026, the average yearly pay for ai rag in Austin, TX is $57,733.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,600.00 and $64,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What are popular job titles related to Ai Rag jobs in Austin, TX? For Ai Rag jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Austin, TX look for? The top searched job categories for Ai Rag jobs in Austin, TX are:
What cities near Austin, TX are hiring for Ai Rag jobs? Cities near Austin, TX with the most Ai Rag job openings:
Infographic showing various Ai Rag job openings in Austin, TX as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $57,733 per year, or $27.8 per hour.

Generative AI Platform Manager, Vice President

State Street

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Job description

About the Role

We're seeking a strategic, hands-on VP to lead the design and delivery of our enterprise Generative AI platform. Primary depth required in AWS Bedrock, Azure AI Foundry, Azure OpenAI, and Databricks, with strong skills in IaC authorship, Harness CI/CD, FinOps, and AI-assisted developer tooling. You'll set technical direction, author production-grade constructs, mentor senior engineers, and enable data scientists and application teams to ship Gen AI solutions at scale.

Key Responsibilities

AWS Bedrock Platform (Primary)

  • Own enterprise Bedrock strategy: model access governance, provisioned throughput, cross-region inference, multi-account architecture
  • Operationalize Knowledge Bases, Agents, Guardrails, Prompt Management, Flows, and Model Evaluation
  • Lead FM lifecycle across Claude, Nova/Titan, Llama, Mistral, and Cohere
  • Design RAG on Bedrock with OpenSearch Serverless, Aurora pgvector, and Kendra
  • Optimize consumption: on-demand vs. PT, model routing, prompt caching, token efficiency

Azure AI Foundry & Azure OpenAI (Primary)

  • Own Foundry hub/project architecture, model catalog governance, and quota management
  • Lead Azure OpenAI patterns (PTU vs. PAYG, capacity planning, content filters) across GPT-4o, GPT-4.1, and o-series models
  • Architect RAG/agent workloads with AI Search, prompt flow, and Agent Service
  • Implement Content Safety, private networking, Entra ID, CMK, and data residency controls

Databricks & Data-Centric AI (Primary)

  • Own Databricks strategy on AWS and Azure: workspace architecture, Unity Catalog, cluster policies
  • Lead Mosaic AI adoption: Model Serving, Vector Search, Feature Store, AI Gateway, MLflow
  • Architect fine-tuning/pretraining pipelines and lakehouse-native RAG on Delta Lake
  • Establish DBU cost controls and serverless governance

Infrastructure as Code & Golden Paths

  • Author L2/L3 CDK constructs (TypeScript/Python), Bicep modules, and Terraform for multi-cloud AI infra
  • Codify secure-by-default "golden paths" enabling teams to launch Gen AI workloads in hours
  • Standardize config-as-code, secrets management, and drift detection

Harness CI/CD

  • Own Harness pipelines, templates, and delegates for Bedrock, Azure OpenAI, Foundry, and Databricks Asset Bundles
  • Integrate with GitOps, Terraform/CDK/Bicep, OPA policy-as-code, and approval gates
  • Establish reference pipelines with linting, security scanning, model eval, and cost checks

Developer Experience

  • Champion Claude Desktop, MCP servers, and AI coding assistants (Copilot, Cursor, Claude Code)
  • Build internal MCP servers exposing enterprise systems to agentic clients
  • Define secure usage patterns for regulated environments; measure productivity impact

Governance & Leadership

  • Establish security, compliance, and responsible AI controls (red-teaming, audit logging, guardrails)
  • Build observability across CloudWatch, Azure Monitor, Databricks system tables, Grafana, Datadog
  • Partner with Data, MLOps, Security, and Application leadership; recruit and mentor a top-tier team
Required Skills
  • Bedrock: Knowledge Bases, Agents, Guardrails, Flows, PT; Claude, Nova, Llama, Mistral; RAG and vector stores (OpenSearch, pgvector, Pinecone, Kendra); agent frameworks (Bedrock Agents, LangGraph, Strands)
  • Azure AI: Foundry hubs/projects, prompt flow, Agent Service; Azure OpenAI (GPT-4o/4.1, o-series, PTU); AI Search; Content Safety
  • Databricks: Mosaic AI, Vector Search, AI Gateway, MLflow, Unity Catalog, Asset Bundles, Delta Lake
  • IaC: CDK L2/L3 (TS/Python), Bicep, Terraform (multi-cloud), secrets management
  • CI/CD: Harness (YAML pipelines, delegates, templates, GitOps), OPA/Rego, GitHub Actions, Azure DevOps
  • FinOps: Token/PTU/DBU governance, tagging, chargeback, capacity planning, token/model optimization
  • Dev Tooling: Claude Desktop, MCP server authoring, Claude Code, Copilot, Cursor
  • Cloud: Deep AWS + Azure (networking, IAM/Entra ID, private endpoints); Docker/Kubernetes (EKS/AKS); serverless; API design; complementary GCP/Vertex AI
  • Data: Delta Lake, Unity Catalog, RAG/fine-tuning data pipelines, governance/lineage
  • Observability: CloudWatch, Azure Monitor, App Insights, Grafana, Arize, Datadog
  • Languages: Python (primary), TypeScript
  • Leadership: Scaling senior teams hands-on, executive communication, owning budgets/roadmaps
Education & Experience
  • Bachelor's or Master's in CS, Engineering, or IT
  • 10+ years in platform/cloud/SRE engineering
  • 5+ years hands-on AWS and Azure with production depth in Bedrock, Azure OpenAI/Foundry, and Databricks
  • 3+ years in technical leadership or people management
  • Financial services or regulated-industry experience strongly preferred
Preferred Qualifications
  • Published CDK construct libraries, Bicep registries, or Terraform modules consumed enterprise-wide
  • Enterprise-scale Harness pipeline authoring and rollout
  • Fine-tuning/continued pretraining experience (LoRA, QLoRA, RLHF, DPO) on Mosaic AI, Azure OpenAI, or Bedrock Custom Models
  • Model optimization: quantization, distillation, prompt caching, speculative decoding
  • PTU/PT capacity planning at scale
  • Production MCP servers and Claude Desktop deployments in regulated environments
  • Agentic frameworks (Bedrock Agents, Azure AI Agent Service, Databricks Agent Framework, LangGraph, Strands)
  • AI safety/guardrail frameworks (Bedrock Guardrails, Azure Content Safety, NeMo, Guardrails AI)
  • Measurable FinOps wins (token/DBU/inference cost reduction)
  • Open-source contributions (CDK, Terraform providers, MCP)
  • Multi-tenant AI platforms with chargeback/showback
  • Board/regulator-level presentation experience
Certifications (one or more preferred)
  • AWS: Solutions Architect Pro, ML Specialty, DevOps Engineer Pro
  • Azure: AZ-305, AI-102, AZ-400, OP-100
  • Databricks: Data Engineer Pro, ML Pro, or Generative AI Engineer Associate
  • GCP: Professional Cloud Architect or ML Engineer (complementary)
  • Harness: Certified Expert (CD or Platform)
  • Anthropic: Claude Builder or partner credentials

Salary Range:

$120,000 - $202,500 Annual

The range quoted above applies to the role in the location specified. If the candidate would ultimately work outside of the location above, the applicable range could differ.

Employees are eligible to participate in State Street's comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.

For a full overview, visit https://hrportal.ehr.com/statestreet/Home.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you'll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

Discover more information on jobs at StateStreet.com/careers

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Job Application Disclosure:

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.


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About State Street

Sourced by ZipRecruiter

State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world. From technology to product innovation, we're making our mark on the financial services industry. For more than two centuries, we've been helping our clients safeguard and steward the investments of millions of people. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Boston, MA, US

Year founded

1792

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