Turing

Remote full-stack React/GCP engineer jobs

We, at Turing, are looking for talented remote full-stack React/GCP engineers who will be responsible for developing user interface components, implementing and executing them following React.js workflow, and deploying applications on GCP. Get this excellent opportunity to collaborate closely with the best minds while working at top U.S. firms.

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Job description

Job responsibilities

  • Collaborate with UI/UX designers, product manager and other team members and stakeholders to plan the roadmap of the full-stack development process
  • Communicate with the tech lead and other engineers to make sound technical decisions
  • Write clean and reusable code that is high performant
  • Follow the standard procedures the company follows within the workflow
  • Participate in website speed optimization on the front-end
  • Evaluate opportunities and learn new technologies, approaches, tools, and skills
  • Participate in front-end code needs refactoring and share feedback

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science, (or equivalent experience)
  • At least 3+ years of experience as a full-stack developer (rare exceptions for highly skilled developers)
  • Strong grasp on JavaScript, including DOM manipulation and the JavaScript object model
  • Extensive knowledge of PostgreSQL database design principle, integrity checks, and query optimization
  • Expert knowledge of stored procedures, functions, triggers, and views in PostgreSQL
  • Solid understanding of React.js and its core principles
  • Extensive working experience with React.js workflows (including Flux or Redux)
  • Prior experience with data structure libraries (e.g. Immutable.js)
  • Good understanding of HTML and CSS
  • Familiarity with RESTful APIs
  • Knowledge of modern authorization mechanisms, like JSON Web Token
  • Fluency in the English language for effective communication
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Working experience with Java/Python
  • Knowledge of isomorphic React
  • GCP certificates are preferred
  • Ability to build rapid prototypes and iterate
  • Have experience working in Agile development environment
  • Good analytical, technical and problem-solving skills
  • Excellent communication and organizational skills

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How to become a Full-stack React/GCP engineer?

React, a JavaScript library for developing user interfaces has gained much traction among developers, and businesses using web applications. React is one of the most popular fields for remote developers seeking jobs related to web apps.

React.js is a popular front-end JavaScript framework that works well with newcomers and startups, as well as engineers who value flexibility. It can smoothly interact with other frameworks, which is a major plus for individuals who want to work without limitations.

Google Compute Platform (GCP) is a set of cloud computing services based on Google App Engine for hosting web applications. GCP has evolved into one of the leading cloud platforms on the market, although it still lags behind Amazon Web Services (AWS) and Microsoft Azure in terms of market share. Google continues to invest in GCP and make it more competitive with other public cloud providers in order to appeal to large clients.

What is the scope of Full-stack React/GCP engineers?

The demand for web- and mobile app-based businesses is high, due to an increase in startups and smart devices in the market. React.js is commonly considered one of the most popular frameworks.

Google Cloud Platform is a collection of infrastructure and platform services that provide developers with a variety of hosted computing, storage, and application services over the public internet or dedicated connection. Google's cloud platform includes over 90 information technology offerings intended to assist enterprises, IT experts, and developers in maximizing productivity, flexibility, and competitive advantage.

Remote Full-stack React/GCP engineer job positions are growing just as quickly as the company's growth. As a result, Full-stack React/GCP engineers will have to put in extra work in researching and developing for users in the future.

What are the roles and responsibilities of a Full-stack React/GCP engineer?

A React developer is involved in all aspects of developing an application from conception to deployment. A React developer should be able to apply his or her understanding of JavaScript, HTML, and CSS to build a solid and effective application in collaboration with product managers, testers, designers, and web developers.

Developers in the Google Cloud Platform (GCP) division are responsible for many tasks, such as designing solution architecture for GCP, representing products in client meetings, and building a product architecture according to the company's needs and requirements. Google Cloud SQL (GCS) will be employed to manage user and customer data.

Full-stack React/GCP engineers must handle several responsibilities, such as:

  • Planning the full-stack development process roadmap with the UX/UI designers, the product manager, and other stakeholders
  • Consult with the tech lead and other engineers before making any technical decisions
  • Ensure your code is clean, reusable, and performant
  • Maintain the workflow by following the standard procedures of the company
  • Optimize the front-end performance of your website
  • Develop new skills and technologies by evaluating opportunities and utilizing new approaches, tools, and techniques
  • Refactor front-end code and share feedback

How to become a Full-stack React/GCP engineer?

Let us now look at the path one must take in order to pursue a profession in the Full-stack React/GCP engineering field. Before you begin your search, remember that there is no requirement of formal educational for becoming a Full-stack React/GCP engineer. One can become proficient in the field of Full-stack React/GCP engineering to create a profession in it whether they are a graduate or non-graduate, experienced or inexperienced. If you have the needed practical experience and command of the relevant technical and non-technical skills, then you can easily score a high paying Full-stack React/GCP engineer job.

Yet, most companies make it mandatory for the candidates to have a bachelor's or master's degree in computer science or a similar discipline to get remote Full-stack React/GCP engineer jobs. This is mainly because of two reasons: first, with the relevant academic background, you can understand computer programming and web development easily, which will help you immensely in learning Full-stack React/GCP engineering. And the next reason is, many firms need candidates to have a specific degree when hiring for Full-stack React/GCP engineer jobs, as it makes it easier for you to get some rewarding work chances.

Now, let's discuss the skills and methods you'll need to master in order to become a successful Full-stack React/GCP engineer:

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Skills required to become a Full-stack React/GCP engineer

The first step is to start learning the fundamental skills that can get you high-paying Full-stack React/GCP engineer jobs. Take a look at what you need to know!

1. Cloud Engineering

In order to get started with cloud computing, you must first learn how different cloud service providers operate. Google Cloud Platform provides end-to-end services such as compute, storage, databases, machine learning, and migration. This makes them a crucial cloud engineer talent in the large data and software development areas. In the GCP community, Google is known for having a stranglehold in large data and software development areas.

2. HTML & CSS

A proficient React developer should be capable of the following:

  • Build and write components that use semantic HTML elements
  • Learn how to write CSS selectors
  • Activate the CSS reset
  • Learn how to use the box model and how to return to border-box mode.
  • You should familiarize yourself with Flexbox

Using responsive web principles, such as media queries, is paramount to the creation of an effective website

3. Cloud Networking

Cloud networking refers to a group of services that allow consumers to access networks via the Internet, rather than maintaining their own computer systems. Because cloud computing relies on the Cloud for storage and data processing, networks that use this method are referred to as cloud networks. The development of cloud-based resources has led to an increase in the level of network administration that can be done remotely, instead of on the user's own computer. This has decreased the need for small-to-medium businesses and home users to have sophisticated and costly computer hardware, because they can use the technology available from a third-party provider.

4. Redux

The React framework uses a concept called state management to create interactive web pages. However, state management can be difficult to understand, especially for beginners. To help overcome this difficulty, Redux, a library built by developers at Facebook and Instagram, was created. Redux allows software engineers to focus on the logic and user requirements of their applications, rather than on the details of the APIs used to create them.

5. Linux

Linux is a common OS in the cloud community because it offers open source, security, and other advantages. Cloud providers are working to make Linux easier to use in the cloud, allowing you to focus on architecting, planning, constructing, managing, and maintaining Linux servers in the cloud. This single cloud Engineer competence might be enough for you to succeed in your career as a GCP developer.

6. Containers

Containers allow applications to run in isolated environments, reducing dependencies on the environment in which they function. Containers, such as those produced by the open source Docker application and the Kubernetes container orchestration engine, are popular tools for deploying applications quickly and reliably.

Interested in remote Full-stack React/GCP engineer jobs?

Become a Turing developer!

Apply now

How to get remote Full-stack React/GCP engineer jobs?

It is extremely rewarding to work as a developer. However, a thorough understanding of programming languages is required. It is recommended that you practise until you get it right. Furthermore, having a product vision is necessary to be in sync with the team. Good communication skills enable team members to collaborate and prioritize work in accordance with the long-term plan.

Turing offers the best remote Full-stack React/GCP engineer jobs that suit your career trajectories as a Full-stack React/GCP engineer. Work on challenging technical and business problems with the latest technologies to grow quickly. Join a network of the world's best developers & get full-time, long-term remote Full-stack React/GCP engineer jobs with better compensation and career growth.

Why become a Full-stack React/GCP engineer at Turing?

Elite US jobs
Career growth
Exclusive developer community
Once you join Turing, you’ll never have to apply for another job.
Work from the comfort of your home
Great compensation

How much does Turing pay their Full-stack React/GCP engineers?

At Turing, every Full-Stack React/GCP engineer is allowed to set their own rate. In any case, Turing will recommend a salary at which we feel we can find a profitable and long-term opportunity for you. Based on our analysis of the market and our customers' demand, we provide recommendations.

Frequently Asked Questions

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Currently, we have openings only for the developers because of the volume of job demands from our clients. But in the future, we might expand to other roles too. Do check out our careers page periodically to see if we could offer a position that suits your skills and experience.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

No, the service is absolutely free for software developers who sign up.

Ideally, a remote developer needs to have at least 3 years of relevant experience to get hired by Turing, but at the same time, we don't say no to exceptional developers. Take our test to find out if we could offer something exciting for you.

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Leadership

In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

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briefcase
Principal AI Engineer - US NYC

Principal AI Engineer

Location: US(NYC)- 3(WFO)

Employment Type: Full Time (Overlapping EST)

Experience Level: Staff/Principal (8–14 years)


About the Role

Turing is hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients. This is a hands-on engineering role focused on designing and shipping autonomous, tool-calling AI systems — agents that reason over enterprise context, invoke real systems through secure interfaces, and operate reliably at scale under strict latency, cost, and governance constraints.

You will own these systems end to end: the data pipelines feeding them, the backend services around them, the agent orchestration layer, the evaluation harness that keeps them honest, and the cloud infrastructure they run on. We are looking for engineers with genuine software engineering and data science depth who have taken agentic systems all the way to production.

What We're Looking For

Engineering foundation

  • 8–14 years of software engineering experience, with strong hands-on large-scale Python
  • Working depth in at least one systems or backend language — Go, Rust, Java, or C/C++ — and the judgment to know when to reach for it
  • Strong data structures and algorithms.
  • Strong understanding of APIs, microservices, and system design
  • Hands-on experience building and operating data pipelines and production-grade distributed systems.

Agentic AI and LLMs

  • 2+ years of hands-on LLM engineering, with at least couple agentic system you designed and took to production
  • Production experience with agent frameworks — LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent — and the fluency to move between them as the ecosystem evolves
  • Experience building MCP (Model Context Protocol) servers and tool-calling interfaces
  • RAG from first principles: chunking strategy, embeddings, vector and hybrid retrieval, reranking, and response validation
  • Strong experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc. or cloud equivalents)
  • Design of guardrails and reliability patterns — validators, policy checks, self-correction loops, deterministic fallbacks, circuit breakers, and rollback paths

Optimization

  • Deep familiarity with token optimization and context-window management — context shaping, pruning, and compaction
  • Latency and cost optimization through caching, model routing, batching, streaming, and parallel tool calls
  • Performance testing and tuning systems against defined SLOs

Evaluation

  • Experience building evaluation frameworks for LLM systems — offline eval sets, continuous online evaluation, and regression detection
  • Instrumentation and traceability suitable for regulated enterprise environments using tools like LangSmith, Langfuse, etc.

Cloud

  • Hands-on AWS: containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift) and orchestration (Step Functions); Azure or GCP equivalents also valued
  • Familiarity with CI/CD pipelines and DevOps practices
  • Infrastructure as code with Terraform or CloudFormation, and mature CI/CD practice

Working traits

  • Strong analytical problem-solving with a bias to ownership and urgency
  • Clear cross-team communication, working directly with client stakeholders to translate business problems into technical roadmaps
  • Able to work productively in ambiguity from system-level documentation and ramp quickly in unfamiliar codebases

Good to Have

  • Experience with managed AI platforms — Amazon Bedrock, Vertex AI, Azure AI — paired with fluency in the underlying fundamentals

Roles & Responsibilities

  • Design and build agentic systems: Lead the architecture and implementation of tool-calling agents that combine retrieval, structured reasoning, and secure action execution with least-privilege access.
  • Productionize LLM applications: Build retrieval pipelines, prompt synthesis, response validation, and self-correction loops, backed by rigorous evaluation.
  • Own the full stack: Deliver the data pipelines, backend services, distributed compute, and orchestration layer that agentic systems depend on — not only the model invocation.
  • Engineer for reliability and governance: Build validator models, adversarial test suites, and policy checks; enforce deterministic fallbacks and rollback strategies; instrument continuous evaluation.
  • Optimize for cost and latency: Drive measurable improvements in token efficiency, response time, and unit economics against defined SLOs.
  • Codebase ownership: Build, maintain, and review high-quality Python and SQL, with an emphasis on reusable components, scalability, and performance.
  • Cloud integration: Deploy AI applications on AWS, Azure, or GCP with optimized resource usage and robust CI/CD.
  • Cross-functional collaboration: Partner with product owners, data scientists, and business SMEs to define requirements and deliver impactful AI products.
  • Mentoring and technical leadership: Set engineering standards and share knowledge across the team, raising the bar on AI and software engineering practice.
Finance
10K+ employees
PythonGoRust+ 4
briefcase
Lead Edge AI & Computer Vision Engineer

Lead Edge AI & Computer Vision Engineer

  • Location: USA [with regular on-site travel required to client site]
  • Target Start Date: 1 Sep
  • Time Commitment: 8 weeks full-time
  • Experience Level: 12–15+ Years

Core Objective: Architect, benchmark, and optimize an end-to-end computer vision and low-latency execution pipeline—combining spatial geometric math with low-level C++/CUDA acceleration directly on NVIDIA Jetson embedded edge hardware (Orin NX / AGX Orin) to achieve sub-10 ms processing latency.

Key Responsibilities

  1. Model Selection & Spatial Math: Evaluate real-time detection topologies (e.g. YOLO) at 100+ FPS and build 2D perspective homography unwarping, lens undistortion, and spatial algorithms to convert pixel coordinates into physical millimeter units within tight error bounds (millimeter level accuracy).
  2. TensorRT INT8 Acceleration: Execute Post-Training Quantization to compile PyTorch/ONNX models into high-throughput TensorRT INT8/FP16 engines on Jetson Orin hardware without accuracy degradation.
  3. Zero-Copy Memory Architecture:  Engineer zero-copy memory pipelines using NVIDIA Memory Management and DMA transfers to eliminate bottlenecks.
  4. Compiled C++ Execution & I/O: Build compiled C++17 execution frameworks with multi-threaded lock-free ring buffers and non-blocking asynchronous socket communication.
  5. Nsight Profiling & Roadmapping: Instrument stage-by-stage pipeline latency using NVIDIA Nsight Systems/NVTX markers to bound tail latency, author feasibility reports, and design technical roadmaps.

Key Qualifications & Experience

  1. Full-Stack Edge AI Experience: 12–15+ years of experience bridging real-time computer vision algorithm design, spatial geometry, and low-level C++/CUDA execution on embedded edge hardware.
  2. NVIDIA Jetson Ecosystem: Deep expertise in Jetson embedded platforms (Orin NX, AGX Orin, L4T, power profiles, core pinning) and a proven track record compiling/tuning TensorRT FP16/INT8 engines via PTQ/QAT.
  3. Optical & Spatial Geometry: Expertise in 2D/3D camera calibration, perspective homography transformations, lens distortion modeling, and millimeter sizing math in industrial settings.
  4. Low-Latency Systems Engineering: Expertise in zero-copy shared memory, DMA frame buffers, lock-free queues, custom CUDA plugins, and microsecond profiling via Nsight Systems and NVTX markers.
  5. Tooling & Industrial I/O: Proficiency in C++17, Python, PyTorch, OpenCV, CUDA, non-blocking asynchronous sockets (UDP, PLC integration), and building automated dataset benchmarking harnesses.
Manufacturing
10K+ employees
C++CUDANVIDIA Omniverse+ 5
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