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Remote Generative Ai Project Manager Jobs in California

Mercor

AI Project Coordinator - GenAI

San Francisco, CA · Remote

$45 - $55/hr

Remote Role Responsibilities * Act as a day-to-day point of contact for AI data projects , ensuring ... Prior people management experience or demonstrated ability to lead large groups effectively.

Mercor

AI Project Coordinator - GenAI

San Francisco, CA · Remote

$45 - $55/hr

Remote Role Responsibilities * Act as a day-to-day point of contact for AI data projects , ensuring ... Strong data management experience with Excel and SQL . * Prior people management experience or ...

Mercor

AI Project Coordinator - GenAI

San Francisco, CA · Remote

$45 - $70/hr

Remote Role Responsibilities * Act as a day-to-day point of contact for AI data projects , ensuring ... Prior people management experience or demonstrated ability to lead large groups effectively.

NYFA

Cinematic AI Specialist

Burbank, CA · On-site +1

$55 - $75/hr

Instructors guide students through the practical and creative applications of generative AI tools ... Remote instruction and project-based learning * Collaborative creative environment New York Film ...

Twenty80 LLC

AI Engineer

San Mateo, CA · Remote

Ability to manage multiple enterprise projects in a fast-paced environment Preferred Qualifications ... Remote-friendly within the United States * Preference for candidates located near major East or ...

Welo Data

Lead Gen AI Analyst

Santa Clara, CA · On-site +1

... Generative AI Analyst to join our team. This leadership role is open to both hybrid and remote ... If you have a strong background in project management, operations, or leading production teams--and ...

TEKsystems

AI Engineer

San Diego, CA · Remote

$50 - $58/hr

Remote AI/ML Software Engineer, Generative AI Are you passionate about building Generative AI systems that move beyond prototypes and create real business impact? A leading healthcare technology ...

Innowhyte Inc

Develop Generative AI solutions, including chatbots, summarization, and content creation tools. Preprocess, clean, and annotate datasets for training and evaluation. Optimize models for performance ...

SAP

SAP iXp Intern - Full-Stack AI Developer

Palo Alto, CA · On-site +1

$22.75 - $29.75/hr

... generative AI hub to integrate and manage foundation models * Design and optimize prompts ... You like to work on meaningful innovative projects and are energized by lifelong learning ...

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Remote Generative Ai Project Manager information

What is a remote generative AI project manager?

Remote Generative AI Project Managers are professionals who oversee projects involving the development and implementation of generative artificial intelligence technologies, such as AI that creates text, images, or other content. They coordinate teams, manage timelines and budgets, and ensure project goals are met—all while working remotely. These managers often act as a bridge between technical teams and stakeholders, making sure projects align with business objectives. Their role requires a blend of project management skills, understanding of AI concepts, and the ability to work effectively in virtual environments.

How does a remote generative AI project manager typically collaborate with cross-functional teams to ensure project success?

Remote Generative AI Project Managers frequently coordinate with data scientists, engineers, product managers, and stakeholders across different locations and time zones. They use a combination of virtual collaboration tools, regular video meetings, and project management platforms to track progress, clarify requirements, and address challenges as they arise. Effective communication and proactive status updates are essential to aligning team efforts, managing expectations, and ensuring timely delivery of AI-driven solutions. Establishing clear workflows and fostering a culture of transparency help maintain momentum and drive successful outcomes, even in a fully remote environment.

What are the key skills and qualifications needed to thrive as a remote generative AI project manager, and why are they important?

To thrive as a Remote Generative AI Project Manager, you need expertise in project management methodologies, a solid understanding of AI concepts, and a relevant degree or certification such as PMP or Agile. Familiarity with AI development tools, collaboration platforms like Jira or Asana, and cloud-based environments is typically required. Outstanding communication, problem-solving abilities, and the capacity to lead cross-functional remote teams are essential soft skills. These competencies ensure effective coordination, timely delivery of AI projects, and seamless collaboration in a remote work environment.

What are popular job titles related to Remote Generative Ai Project Manager jobs in California?

For Remote Generative Ai Project Manager jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Project Manager jobs in California look for?

The top searched job categories for Remote Generative Ai Project Manager jobs in California are:

What cities in California are hiring for Remote Generative Ai Project Manager jobs?

Cities in California with the most Remote Generative Ai Project Manager job openings:

Remote Generative Ai Project Manager jobs near you
Infographic showing various Remote Generative Ai Project Manager job openings in California as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Senior Generative AI Engineer (Google Gemini & Vertex AI) - Remote

San Diego, CA • On-site, Remote

DivIHN
See more jobs at DivIHNexternal

$110K - $152K/yr

Contractor

Posted 7 days ago

Job description

For further inquiries about this opportunity, please contact one of our Talent Specialists, Justeen at (224)-394-4903
Title: Senior Generative AI Engineer (Google Gemini & Vertex AI) - Remote
Duration: 6 Months with possible for extension
Location: Remote
Candidates must be available to work West Coast (PST) hours.
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.
Day to Day Responsibilities
  • RAG & Prompt Engineering: Craft and refine effective prompts for RAG, grounding, and context tuning to achieve optimal AI performance in product development.
  • High-Performance API Engineering: Develop asynchronous microservices (FastAPI) using Server-Sent Events (SSE) or WebSockets to stream real-time LLM responses to front-end UIs without backend timeouts.
  • Vector Database Infrastructure: Design, develop, and implement robust Vector Databases using LLMs and modern retrieval technologies to capture information from diverse engineering sources (PDFs, design docs, regulatory guidelines).
  • Data Extraction & Structuring Pipelines: Build and optimize pipelines to extract and structure multi-modal data (tables, text, images) from unstructured documents for LLM training, grounding, and runtime query execution.
  • LLM Fine-Tuning & Training: Fine-tune and train generative AI models using client's engineering data and domain knowledge to create high-accuracy, domain-specific models.
  • GenAI Application & Tool Development: Design and implement scalable backend APIs (FastAPI/REST) and UI integration interfaces so internal engineers can query knowledge bases and analyze data.
  • Automated Requirements Generation: Develop backend functionalities to automatically generate technical requirements from design documents, user stories, and system specification files.
  • Documentation & Knowledge Transfer: Thoroughly document architecture, code, REST endpoints, and model training procedures to enable seamless knowledge transfer to client's internal teams.
  • Cross-Functional Collaboration: Partner closely with Subject Matter Experts (SMEs), System Engineers, and V&V Test teams to optimize AI-powered workflows.
  • AI Guardrails, MLOps & Cost Governance: Implement hallucination checks, PII masking, and guardrails (e.g., NeMo Guardrails) for medical device context. Track token usage, latency, and costs using LangSmith or Vertex AI monitoring.
  • Collaborate closely with engineers and cross-functional teams to design and develop AI solutions.
  • Develop and integrate Generative AI applications and APIs.
  • Work with large datasets, document processing, and data pipelines.
  • Participate in problem-solving, solution design, and technical discussions.
  • Communicate effectively with team members and stakeholders.

Must-Have Qualifications :
  • Relevant Experience & STEM Foundation: 4+ years of professional software/ML engineering experience, with a dedicated AI/ML focus in the last 1-2 years.
  • Google Gemini / Vertex AI (Non-negotiable): Hands-on experience with the Gemini model family and Vertex AI, including deployment, grounding, and integration into production AI services. Hands-on experience with containerization (Docker) and deploying services via Cloud Run or GKE (Kubernetes).
  • Languages & AI Libraries: Proficiency in Python and modern ML/AI frameworks (PyTorch, LangChain, LangSmith) for building autonomous LLM agents, tools, and RAG pipelines.
  • Agent Building & Tool Calling: Proven experience building AI/LLM agents and tool-calling systems in Python against unstructured, multi-source data.
  • Context Engineering & RAG: Expertise in RAG pipelines, prompt engineering, context tuning, grounding, and Vector Databases (e.g., Milvus, Postgres/Pgvector). Clear understanding of advanced RAG architecture including Hybrid Search (Vector + Keyword), Re-ranking models, and semantic caching.
  • Unstructured Data Handling (Non-negotiable): Demonstrated ability to ingest, clean, extract, and structure text, tables, and images from unstructured documents (PDFs, design docs, regulatory files) for LLM training and usage.

Role Information
  • Generative AI Engineer role.
  • Experience in API development.
  • Hands-on experience with Google Gemini and Vertex AI.
  • Knowledge of Agentic AI frameworks and architectures.
  • Strong Python development skills, including experience with LangChain and related AI frameworks.
  • Open to candidates from any industry domain.

Required Skills :
  1. Full Stack Engineering - Building applications for AI-powered services (Backend APIs + Front-End Integration).
  2. Generative AI & LLM Platforms - 2+ years building RAG pipelines & LLM apps using Python, LangChain, and LangSmith.
  3. Agent Building & Unstructured Data - Building AI agents/tool-calling systems in Python and handling unstructured, multi-source data extraction (PDFs, docs).
  4. Strong hands-on experience in Artificial Intelligence and Generative AI
  5. Python programming expertise.
  6. Experience with LangChain and Agentic AI frameworks.
  7. Understanding data handling to pull data from PDFs, design docs, regulatory files

Preferred Skills :
  1. Direct experience architecting and serving custom REST APIs.
  2. Experience in regulated / compliance-sensitive domains (e.g., healthcare / medical device guidelines like FDA, ISO 13485).
  3. Experience integrating multiple LLM APIs beyond a single provider (OpenAI, Bedrock, Claude, or similar).

Additional Preferred Skills
  • Direct experience designing and deploying high-throughput REST APIs (e.g., FastAPI/Flask).
  • Familiarity with medical device development regulations and compliance (e.g., FDA guidelines, ISO 13485).
  • Experience integrating multiple LLM APIs beyond a single vendor (e.g., OpenAI, AWS Bedrock, Anthropic Claude).
  • Front-end development/integration experience for UI design (e.g., Streamlit, Gradio, React/Next.js integration).

Education Requirements:
  • Minimum Bachelors in Software/Computer/IT/Systems/Biomedical Engineering + 3 years

Required Testing:
  • Technical evaluation of Python proficiency, RAG architecture concepts, and API/Agent design.

Software Skills Required:
  • Languages: Python (AsyncIO, OOP), SQL.
  • AI & Agent Frameworks: PyTorch, LangChain, LangSmith, Vertex AI SDK.
  • API & Web Frameworks: FastAPI, Flask, REST APIs, Server-Sent Events (SSE).
  • Databases & Search: Milvus, Pgvector, Qdrant, Redis (caching).
  • Front-End Integration: Streamlit, Gradio, basic React/Next.js.
  • Testing & Guardrails: pytest, JUnit, LangSmith evaluation, NeMo Guardrails.
  • DevOps & Cloud: Docker, GCP (Vertex AI, Cloud Run, GKE), Git.

Required Certifications:
  • Professional certifications specific to AI/ML (e.g., Certified AI Professional / CAIP, Google Cloud ML Engineer) considered a plus.

Interview
  • Number of Interviews: 1,
  • Web Conference (Zoom/ TEAMs)
  • Live problem-solving and technical exercise during the interview.

Apply