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Remote Google Apps Script Developer Jobs in San Diego, CA

TEAM

Full Stack Developer

San Diego, CA · On-site +1

Job type: Full Time / Hybrid (2 days remote, 3 days in office) Location: 3131 Camino del Rio N, Ste ... Proficiency in Azure Cloud Services (Function Apps, Logic Apps, Service Bus, Entra ID, etc.

Mondo

Social Content Writer

San Diego, CA · Remote

$25 - $30/hr

Remote (weekly check-in meeting required) Start Date: Mid-August Duration: Ongoing Contract ... Draft video scripts and supporting copy for crew-of-the-month features and similar spotlight ...

AbacusNext

Senior Infrastructure Engineer

San Diego, CA · On-site +1

$130K - $160K/yr

Design, implement, and own automation scripts using PowerShell and infrastructure-as-code tools ... Use code management repositories (e.g., GitHub, Azure DevOps) for infrastructure configuration and ...

Gunderson LLC

Systems Integration Developer

San Diego, CA · On-site +1

$150K - $180K/yr

Familiarity with Azure services including Logic Apps, Azure AD, Data Factory, SQL, App Services ... Hybrid schedule, may be considered for remote eligible The annualized base salary range for this ...

Wsgr

Principal Cloud Infrastructure Engineer

San Diego, CA · On-site +1

$147K - $198K/yr

This role can be hybrid or virtual/remote. Essential Duties and Responsibilities: * Act as the ... Experience with Power Platform, Azure DevOps, Foundry, Copilot, Graph API, Logic Apps, Function ...

Adidev Technologies Inc

IOSDeveloper

San Diego, CA · On-site +1

$30 - $40/hr

Must be open to working onsite, no telecommuting/remote positions are being offered. Must be a ... As an iOS or Android Mobile Developer for Adidev Technologies Inc., you will be enhancing and ...

Hired Recruiters

Senior Software Engineer

San Diego, CA · Remote

$120K - $180K/yr

Location: 100% US/Canada remote * In Office Locations: San Francisco, San Diego, Toronto * ~60 ... Familiarity with databases (MySQL, MongoDB) and devOps (GitHub, Docker, AWS, Google Compute Engine)

SAIC

Data Ops Engineer

San Diego, CA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description We are seeking a Data Ops Engineer to ... DevOps roles supporting production data pipelines. Tools * Apps/Platforms: NiFi, Kafka, Grafana ...

DataAnnotation

Programmer - AI Trainer

Carlsbad, CA · On-site +1

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

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Showing results 1-20

All JobsGoogle Apps Script Developer JobsRemote Google Apps Script Developer JobsRemote Google Apps Script Developer Jobs in San Diego, CA

Remote Google Apps Script Developer information

See San Diego, CA salary details

$31.3K

$113.2K

$179.4K

How much do remote google apps script developer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote google apps script developer in San Diego, CA is $113,161.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,100.00 and $135,900.00 per year, depending on experience, location, and employer.

What is a remote Google Apps Script developer?

A Remote Google Apps Script Developer is a professional who writes, customizes, and manages Google Apps Script code to automate tasks and enhance the functionality of Google Workspace applications like Google Sheets, Docs, and Drive, all while working from a remote location. They use JavaScript-based scripting to build custom workflows, integrations, and add-ons that improve efficiency and collaboration for organizations. These developers can work as freelancers, contractors, or full-time employees, collaborating with teams virtually using online tools. Their expertise helps businesses save time and reduce manual work by leveraging automation within the Google ecosystem.

What are the key skills and qualifications needed to thrive as a remote Google Apps Script developer?

To thrive as a Remote Google Apps Script Developer, you need strong JavaScript programming skills, experience with Google Workspace APIs, and a relevant degree or equivalent work experience. Familiarity with Google Apps Script IDE, version control systems like Git, and knowledge of cloud-based deployment workflows are commonly expected. Effective problem-solving, self-motivation, and clear remote communication are standout soft skills in this role. These skills ensure efficient development, seamless automation of workflows, and successful collaboration in distributed teams.

What are the common challenges faced by remote Google Apps Script developers, and how can they be addressed?

Remote Google Apps Script Developers often encounter challenges such as communicating effectively with distributed teams and managing project requirements across different time zones. Additionally, ensuring the security and scalability of scripts within the Google Workspace environment can be complex. To address these challenges, developers should leverage collaboration tools like Google Meet and Slack, maintain clear documentation, and adhere to best practices for script deployment and access control. Regular check-ins and code reviews also help maintain alignment and code quality within the team.

What is the difference between Remote Google Apps Script Developer vs Remote Excel VBA Developer?

AspectRemote Google Apps Script DeveloperRemote Excel VBA Developer
Required CredentialsBasic programming knowledge, Google account familiarityProficiency in VBA, Microsoft Office certifications
Work EnvironmentGoogle Workspace, cloud-based toolsMicrosoft Office, desktop or cloud-based Excel
Industry UsageAutomation within Google Sheets, Docs, DriveExcel automation, macros, data analysis
Common Search/ComparisonOften compared for cloud vs desktop automation rolesRelated but more desktop-focused

Remote Google Apps Script Developers focus on automating Google Workspace apps using JavaScript, while Remote Excel VBA Developers specialize in automating Excel with VBA macros. Both roles require scripting skills but differ in platform and environment, making them distinct yet comparable in automation tasks within their respective ecosystems.

What are popular job titles related to Remote Google Apps Script Developer jobs in San Diego, CA?

For Remote Google Apps Script Developer jobs in San Diego, CA, the most frequently searched job titles are:

What job categories do people searching Remote Google Apps Script Developer jobs in San Diego, CA look for?

The top searched job categories for Remote Google Apps Script Developer jobs in San Diego, CA are:

What cities near San Diego, CA are hiring for Remote Google Apps Script Developer jobs?

Cities near San Diego, CA with the most Remote Google Apps Script Developer job openings:

Remote Google Apps Script Developer jobs near you
Infographic showing various Remote Google Apps Script Developer job openings in San Diego, CA as of June 2026, with employment types broken down into 73% Full Time, 10% Part Time, and 17% Contract. Highlights an 100% Remote job distribution, with an average salary of $113,161 per year, or $54.4 per hour.

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

DivIHN

San Diego, CA • On-site, Remote

$110K - $152K/yr

Contractor

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Develop asynchronous microservices using FastAPI with SSE or WebSockets to stream real-time LLM responses to front-end UIs.

  • Design, develop, and implement vector database infrastructure to capture information from diverse engineering sources.

  • Build and optimize data extraction and structuring pipelines for multi-modal data from unstructured documents.

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