Top 50 Retrieval augmented generation retrieval augmented generation model tuning Jobs in San Francisco, Ca

AWS AI Engineer / USC and GC Candidates can ONLY Apply
Hudson Manpower —San Francisco Bay Area, CA
- Full-time
- Remote
- 7 years
- System design
- English
- Profit sharing
- Paid training
Quick Apply
JR. AI ENGINEER
Revi —San Francisco, CA
- $130,000 - $170,000 a year
- Full-time
- Azure
- Computer Science
- Bachelor of Science
- Paid holidays
- Health insurance
Quick Apply
Analyst, Quant Research
BlackRock Investments —San Francisco, CA
- $111,625 - $132,500 a year
- Hybrid work
- Office
- SQL
- Children
- Health insurance
- Tuition reimbursement
1d
Sr. AI Architect
Cognizant —San Francisco, CA
- $174,500 - $204,500 a year
- Full-time
- Hybrid work
- 11+ years
- Databases
- Mentoring
- Paid parental leave
- Employee stock purchase plan
9d
ASSOCIATE, DATA ENGINEER
Cresset Capital —San Francisco, CA
- $85,000 - $110,000 a year
- Computer Science
- Mid-level
- AWS
- Health savings account
- Disability insurance
Quick Apply
Data Engineer (Founding Team)
Fabrion —San Francisco Bay Area, CA
- Full-time
- System design
- Senior level
ML/AI Founding Engineer
Navi AI —San Francisco, CA
- Full-time
- 5 years
- System design
- Analysis skills
Applied AI Engineer
Ramp —San Francisco, CA
- $204,400 - $352,000 a year
- Full-time
- Hybrid work
- Fair chance
- Senior level
- Travel reimbursement
- AD&D insurance
ML/AI Research Engineer — Agentic AI Lab (Founding Team)
Fabrion —San Francisco Bay Area, CA
- Full-time
- Research
- SQL
- Continuous improvement
AI Engineer
Zyphra —San Francisco, CA
- Full-time
- System design
- Mid-level
- Office
- Health insurance
- Dental insurance
ML Ops Engineer — Agentic AI Lab (Founding Team)
Fabrion —San Francisco Bay Area, CA
- Full-time
- DevOps
- HIPAA
- Mid-level
Applied AI Engineer
Serval —San Francisco, CA
- $200,000 - $325,000 a year
- Full-time
- Computer Science
- System design
- Mid-level
Google Data Specialist
Accenture —San Francisco, CA
- $59,100 - $196,000 a year
- Full-time
- Hybrid work
- SQL
- US work authorization
- Military encouraged
- Paid holidays
- Disability insurance
AI Engineer (Mid-Level)
Clera —San Francisco, CA
- Full-time
- Remote
- Mid-level
- AWS
- 2 years
Quick Apply
Agentic AI Engineer
GeoDelphi —San Francisco, CA
- Remote
- Computer Science
- 5 years
- Master's degree
- Paid parental leave
- Paid holidays
Quick Apply
Senior Applied Researcher
Apple —San Francisco, CA
- $184,700 - $324,800 a year
- Computer Science
- Doctor of Philosophy
- Mentoring
- Employee stock purchase plan
- Health insurance
Staff Machine Learning Engineer
Databricks —San Francisco, CA
- $190,000 - $285,000 a year
- Mid-level
- Office
- Analysis skills
AI Research Scientist, CoreML - Monetization
Meta —San Francisco, CA
- $184,000 - $257,000 a year
- Mid-level
- 3 years
- US work authorization
Principal Engineer, AI Systems
Block, Inc. —San Francisco Bay Area, CA
- $319,000 - $478,600 a year
- Remote
- System design
- 11+ years
- Mentoring
- Life insurance
- Retirement plan
AWS Cloud Technical Architect – Gen AI
WinWire —Alameda, CA
- $10 - $12 an hour
- Full-time
- 5 years
- Mentoring
- In-person

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AWS AI Engineer / USC and GC Candidates can ONLY Apply

Hudson Manpower
San Francisco Bay Area, CA

Quick Apply

Job Details

Full-time

Benefits

Profit sharing
Paid training
Disability insurance
Health insurance
Dental insurance
Vision insurance
401(k) matching
Referral program

Qualifications

AI models
Function as a Service (FaaS)
Software engineering
Tooling
Infrastructure as Code (IaC)
Amazon ECS
Software implementation
Amazon SageMaker
Generative models
Application deployment
AI platforms (beyond public GPTs)
Computational framework
Enterprise software systems development
Production systems
Machine learning cloud services
Machine intelligence
Model deployment
Version control systems
Terraform
Developing large-scale AI models
System deployment
Cloud automation
Cloud solution engineering
DevOps automation
Machine learning libraries
Machine learning frameworks
MLOps
Generative AI
Providing code feedback
AWS Lambda

Full Job Description

Job Title: AWS AI Engineer

Location: REMOTE USA

TOP SKILLS:
Must Have

AWS services- Bedrock, SageMaker, ECS and Lambda

Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config)

Experience implementing RAG architectures and using frameworks and ML tooling like: Transformers, PyTorch, TensorFlow, and LangChain

Experience in Infrastructure as Code best practices and experience with building Terraform modules for AWS cloud

Fine-tuning large language models, building datasets and deploying ML models to production

Git-based version control, code reviews, and DevOps workflows

Nice To Have

AWS or relevant cloud certifications

Data privacy and compliance best practices (e.g., PII handling, secure model deployment)

Data science background or experience working with structured/unstructured data

Exposure to FinOps and cloud cost optimization

Hugging Face, Node.js

Policy as Code development (I.e. Terraform Sentinel)

What You’ll Do

GENERAL FUNCTION:
We are hiring a Sr AI AWS Engineer who has actually built AI/ML applications in cloud—not just read about them. This role centers on hands-on development of retrieval-augmented generation (RAG) systems, fine-tuning LLMs, and AWS-native microservices that drive automation, insight, and governance in an enterprise environment. You’ll design and deliver scalable, secure services that bring large language models into real operational use—connecting them to live infrastructure data, internal documentation, and system telemetry.

You’ll be part of a high-impact team pushing the boundaries of cloud-native AI in a real-world enterprise setting. This is not a prompt-engineering sandbox or a resume keyword trap. If you’ve merely dabbled in BedRock, mentioned RAG on LinkedIn, or read about vector search—this isn’t the right fit. We’re looking for candidates who have architected, developed, and supported AI/ML services in production environments.

This is a builder’s role within our Public Cloud AWS Engineering team. We aren’t hiring buzzword lists or conference attendees. If you’ve built something you’re proud of—especially if it involved real infrastructure, real data, and real users—we’d love to talk. If you’re still learning, that’s great too—but this isn’t an entry-level role or a theory-only position.

DUTIES AND RESPONSIBILITIES:
Hands-on role using AWS (Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, S3).

Responsible for the implementation of AWS cloud services including infrastructure, machine learning, and artificial intelligence platform services.

Experience with LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other frameworks.

Develop cloud-native microservices, APIs, and serverless functions to support intelligent automation and real-time data processing.

Collaborate with internal stakeholders to understand business goals and translate them into secure, scalable AI systems.

Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code (Terraform).

Support the development and evolution of reusable platform components for AI/ML operations.

Create and maintain technical documentation for the team to reference and share with our internal customers.

Excellent verbal and written communication skills in English.

SUPERVISORY RESPONSIBILITIES: None

MINIMUM KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:
7 years of hands-on software engineering experience with a strong focus on Python.

Experienced with AWS services, especially Bedrock or SageMaker

Familiar with fine-tuning large language models or building datasets and/or deploying ML models to production.

Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config).

Solid experience implementing RAG architectures and LangChain.

Demonstrated experience in Infrastructure as Code best practices and experience with building Terraform modules for AWS cloud.

Strong background in Git-based version control, code reviews, and DevOps workflows.

Demonstrated success delivering production-ready software with release pipeline integration.

Nice-to-Haves:
AWS or relevant cloud certifications.

Policy as Code development (e.g., Terraform Sentinel).

Experience with Hugging Face, Golang, or Node.js.

Exposure to FinOps and cloud cost optimization.

Data science background or experience working with structured/unstructured data.

Awareness of data privacy and compliance best practices (e.g., PII handling, secure model deployment).

What You’ll Get

Competitive base salary

Medical, dental, and vision insurance coverage

Optional life and disability insurance provided

401(k) with a company match and optional profit sharing

Paid vacation time

Paid Bench time

Training allowance offering

You’ll be eligible to earn referral bonuses!

Quick Apply

Refine Your Search

retrieval augmented generation retrieval augmented generation model tuning jobs in san francisco, ca

AWS AI Engineer / USC and GC Candidates can ONLY Apply

JR. AI ENGINEER

Analyst, Quant Research

Sr. AI Architect

ASSOCIATE, DATA ENGINEER

Data Engineer (Founding Team)

ML/AI Founding Engineer

Applied AI Engineer

ML/AI Research Engineer — Agentic AI Lab (Founding Team)

AI Engineer

ML Ops Engineer — Agentic AI Lab (Founding Team)

Applied AI Engineer

Google Data Specialist

AI Engineer (Mid-Level)

Agentic AI Engineer

Senior Applied Researcher

Staff Machine Learning Engineer

AI Research Scientist, CoreML - Monetization

Principal Engineer, AI Systems

AWS Cloud Technical Architect – Gen AI

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