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How much do gatsby js jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for gatsby js in the United States is $58.23, according to ZipRecruiter salary data. Most workers in this role earn between $49.28 and $63.70 per hour, depending on experience, location, and employer.

What is a Gatsby JS?

A Gatsby.js job involves developing high-performance websites and applications using Gatsby, a React-based static site generator. Developers in this role build fast, secure, and scalable web experiences by leveraging GraphQL for data fetching and optimizing site performance. Typical responsibilities include creating reusable components, implementing SEO best practices, and integrating data from various sources like CMSs or APIs. Proficiency in React, Node.js, and front-end technologies is often required.

What does a Gatsby JS developer do?

As a Gatsby.js Developer, you’ll typically be involved in building and maintaining fast, static websites or web applications, often collaborating closely with design teams to transform mockups into responsive, high-performance user interfaces. Daily responsibilities commonly include integrating data from various sources using GraphQL, optimizing sites for speed and SEO, managing deployments, and maintaining code using tools like Git. You may also troubleshoot performance issues, develop custom plugins or themes, and participate in code reviews. Most projects require clear communication with other developers, designers, and sometimes clients, making teamwork a vital part of the role.

What are the key skills and qualifications needed to thrive as a Gatsby JS developer?

To excel as a Gatsby.js Developer, you need a solid understanding of JavaScript, React, and modern web development fundamentals, often backed by a degree in Computer Science or related experience. Mastery of GraphQL, static site generators, and version control systems like Git is highly beneficial, while certifications in front-end frameworks can provide an added advantage. Strong problem-solving, attention to detail, and effective communication skills help developers collaborate seamlessly with designers and other team members. These skills ensure the delivery of fast, scalable, and maintainable web solutions that meet project goals and client expectations.

What are the most commonly searched types of Gatsby Js jobs?

The most popular types of Gatsby Js jobs are:

Infographic showing various Gatsby Js job openings in the United States as of September 2026, with employment types broken down into 90% Full Time, 4% Part Time, and 6% Contract. Highlights an 71% Physical, 5% Hybrid, and 24% Remote job distribution, with an average salary of $121,124 per year, or $58.2 per hour.

ML Search Engineer

Birmingham, AL • On-site

Seneca Resources Company, LLC
IT Services • 51 - 200 employees

$130K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 19 days ago


Job description

Position Title: Full Stack Engineer - AI Search & Product Discovery
Location: Remote
Position Status: Full Time
About the Role
We're transforming how millions of industrial buyers discover products through intelligent search experiences powered by AI, machine learning, and modern search technologies.
As a Full Stack Engineer III on our AI Search & Product Discovery team, you'll build the frontend applications, backend services, and search infrastructure that power highly relevant, personalized search experiences at scale. You'll work across the full development lifecycle, from rapid prototyping and experimentation to deploying production-grade solutions and continuously optimizing performance based on real user behavior.
This is an ideal opportunity for an engineer who enjoys solving complex problems at the intersection of full-stack development, search engineering, cloud-native architecture, machine learning, and AI-driven user experiences.
What You'll Do
Build AI-Powered Search Experiences
  • Design, develop, and deploy scalable Python services that power search retrieval, ranking, recommendation, and discovery experiences.
  • Build and integrate machine learning inference pipelines, including embeddings, transformer models, query understanding, reranking services, and LLM-powered features.
  • Develop robust APIs and microservices that support high-volume search workloads and customer-facing applications.
  • Collaborate with product, engineering, and AI teams to translate business goals into impactful search solutions.
  • Continuously improve search relevance, performance, and user engagement through experimentation and data-driven decision making.

Develop Modern Full-Stack Applications
  • Build responsive, accessible, and performant user interfaces using React and modern JavaScript frameworks.
  • Create reusable frontend components and establish engineering standards that improve consistency and developer productivity.
  • Partner with UX and Product teams to transform wireframes and Figma designs into intuitive customer experiences.
  • Contribute to frontend architecture decisions that support long-term scalability and maintainability.

Advance Search & AI Infrastructure
  • Implement hybrid search architectures that combine keyword search, vector search, semantic retrieval, and AI-powered ranking.
  • Build and maintain Elasticsearch/OpenSearch indexing pipelines, query services, and relevance tuning capabilities.
  • Integrate vector databases and retrieval systems such as Pinecone, Weaviate, FAISS, or similar technologies.
  • Develop and optimize Retrieval-Augmented Generation (RAG) and LLM-powered search workflows.
  • Instrument search systems with meaningful metrics, including click-through rate, latency, engagement, and zero-result rates to drive ongoing optimization.

Build Cloud-Native Systems
  • Develop event-driven, distributed systems using Google Cloud Platform (GCP) services such as Cloud Run, GKE, Pub/Sub, and Cloud Functions.
  • Deploy, monitor, and maintain production services using modern DevOps and observability practices.
  • Own service reliability through testing, monitoring, troubleshooting, and operational excellence.

Contribute to Engineering Excellence
  • Participate in architecture discussions, technical design reviews, and code reviews.
  • Mentor peers through collaboration and knowledge sharing.
  • Champion engineering best practices, software craftsmanship, and continuous improvement.

Required Qualifications
  • 4+ years of professional experience in Full Stack Engineering, Backend Engineering, or Software Development.
  • Strong hands-on experience building applications with Python and React.
  • Experience with modern frontend frameworks such as Next.js, Remix, Vite, Gatsby, or similar technologies.
  • Proven experience building and supporting scalable microservices, REST APIs, and/or gRPC services.
  • Experience deploying and operating cloud-native applications in GCP, AWS, or Azure.
  • Experience with Docker, containerized applications, and serverless architectures.
  • Strong understanding of software design patterns, SOLID principles, testing strategies, and maintainable code practices.
  • Experience working with relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, DynamoDB, or similar platforms.
  • Strong communication skills with the ability to collaborate effectively across engineering, product, and architecture teams.
  • Comfortable leveraging AI-assisted development tools to improve productivity and quality.

Preferred Qualifications
Search Engineering
  • Elasticsearch, OpenSearch, Solr, Algolia, or other enterprise search platforms.
  • Search relevance tuning, query optimization, indexing strategies, and ranking algorithms.
  • Large-scale search infrastructure and information retrieval systems.

AI & Machine Learning
  • Generative AI, Large Language Models (LLMs), and AI-powered search experiences.
  • Retrieval-Augmented Generation (RAG).
  • Prompt engineering and LLM orchestration.
  • LangChain, LangGraph, Google ADK, or similar frameworks.
  • Machine learning model deployment and inference pipelines.

Vector Search & Semantic Retrieval
  • Embeddings and semantic search architectures.
  • Approximate Nearest Neighbor (ANN) search.
  • Pinecone, Weaviate, FAISS, Milvus, or similar vector database technologies.

Additional Experience
  • Monorepo development environments.
  • Event-driven architectures.
  • Distributed systems at scale.
  • A/B testing and experimentation frameworks.

About Seneca Resources:
At Seneca Resources, we are more than just a staffing and consulting firm, we are a trusted career partner. With offices across the U.S. and clients ranging from Fortune 500 companies to government organizations, we provide opportunities that help professionals grow their careers while making an impact.
When you work with Seneca, you're choosing a company that invests in your success, celebrates your achievements, and connects you to meaningful work with leading organizations nationwide. We take the time to understand your goals and match you with roles that align with your skills and career path. Our consultants and contractors enjoy competitive pay, comprehensive health, dental, and vision coverage, 401(k) retirement plans, and the support of a dedicated team who will advocate for you every step of the way.