Turing

Remote back-end integrations engineer jobs

We, at Turing, are looking for talented remote back-end integrations engineers who will be primarily responsible for conducting project reviews and evaluating patches to design automation software and plan for release management. Here's your chance to collaborate with top industry leaders while working with top Silicon Valley companies.

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Job description

Job responsibilities

  • Develop integration interfaces across different platforms
  • Develop back-end code to integrate with third party hardware and software APIs through REST, SOAP and/or Vendor SDKs
  • Collaborate with external teams to develop solutions to meet customer demands
  • Assist with the synchronization and automated testing
  • Support back-end integration configuration by developing front-end code
  • Participate actively in building public APIs
  • Assist engineering team to build microservices using Docker and AWS
  • Participate in quality software development
  • Contribute to code review and share constructive feedback
  • Ensure promoting high quality and engineering best practices

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • 3+ years of experience in back-end/system integration (rare exceptions for highly skilled developers)
  • Hands-on experience in back-end API integration and testing
  • In-depth knowledge of protocols like NTP, PTP, TCP, UDP
  • Solid expertise in C and C++14 or above
  • Solid understanding of enterprise APIs and processes
  • Excellent back-end development skills using programming languages like Python, Java, PHP, Ruby, etc.
  • Efficiency in RESTful API design and documentation
  • Fluent in English to communicate effectively
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Proficient in using JavaScript and Node.js in web applications
  • Remarkable expertise in security, web standards, and architecture
  • Clear idea about principles of software design and architecture
  • Familiarity with relational database concepts
  • Understanding of MuleSoft, Kong or similar API technologies
  • Knowledge of Agile, DevOps methodologies
  • Great technical, analytical and problem-solving skills

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How to become a remote Backend integrations engineer in 2023?

The world of customer-facing software and applications is dictated by evolving user-preference patterns. To cope with changing needs and scaling requirements, the use of integrations is quite common in the present industry. In the past decade, the utilization of third-party integrations has significantly increased. This has allowed developers to quickly configure essential features and key functions to make applications more usable. For which, the importance of Backend integrations engineers has also increased in the market.

Based on the importance of assembling a team fit to address the requirements of modern applications, companies actively try to find developers capable of taking ownership of tasks. In the current industry, Backend integrations engineers are high-value professionals capable of driving several development processes. The right hiring can allow a team to build more efficient applications with the potential of becoming the preferred choice. So, for developers looking to find success working as a Backend integrations engineer, the future can be filled with new opportunities.

What is the scope in back-end integrations engineering?

The rising importance of remote access and digitally-enabled services will present backend development experts with plenty of opportunities in the decade ahead. With a growing number of users joining the digital revolution every day, the demand for experts has also increased. Backend developers specializing in integration processes and the right set of skills can easily secure the best jobs in the market.

Backend integrations are an important part of every development process and need to be scalable to fit an evolving market. Also with an increasing number of new third-party plugins and extensions making software development seamless, a deep understanding of integration processes will be defining skills. So, if you’re looking to take your career ahead as a back-end integrations engineer, stay updated about the latest developments and releases. Also, keep scaling up your knowledge of working with associated technologies.

What are the responsibilities and roles of a back-end integrations engineer?

When hired for back-end integrations engineer jobs, expect to contribute to almost every aspect of the back-end development processes. Top tech firms always try to hire back-end integration developers with a few years of professional experience. Such hirings are often beneficial as experienced developers also present the chance to find future leaders. As a back-end integrations engineer expect to be closely associated with tasks like third-party integrations, test automation setups, assisting in code reviews, and more. You will also need to pay close attention to project specifications to understand essential backend services and prioritize development processes. You may also have to collaborate with front-end team members to produce optimized features.

If you’re looking to work as a Backend integrations engineer, expect daily responsibilities to include tasks like:

  • Build interfaces for integration across different platforms
  • Write back-end codes for integrating third-party hardware and APIs using REST, SOAP, or Vendor SDKs
  • Work closely with external teams to develop solutions utilizing customer preferences
  • Contribute to synchronization and automated testing processes
  • Assist back-end integrations by writing efficient front-end codes
  • Actively contribute to building public APIs
  • Work with engineering teams to build microservices using Docker and AWS
  • Participate in quality software development
  • Perform scheduled code review and provide constructive feedback
  • Implement high-quality engineering best practices

How to become a back-end integrations engineer?

Back-end integrations are a vital part of every software development project and require a thorough understanding of industry standards. To find success in such roles, you need to be familiar with API integration and testing processes and protocols like NTP, PTP, etc. You are also expected to possess expertise in working with several modern programming languages used for building customer-facing applications. Along with knowledge of programming backend integrations, you should also be able to communicate with confidence. Interpersonal skills play a huge part in the modern work culture, especially with remote positions becoming more common. A degree in Computer Science or related fields will also find it easier to secure the best openings at top companies.

Professionals with a skillset covering every aspect of backend development and integrations can build a successful career. As a developer specializing in backend development, you should also have a fair understanding of user preferences to devise the right logic for every niche product. To get a detailed idea about the primary skills required to find success in a back-end integrations engineer, check out the following section.

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Skills required to become a back-end integrations engineer

In order to build a successful career as a back-end integrations engineer, developers need to possess expertise in working with technologies. To work as a back-end integrations engineer you’ll need to develop capabilities of working with the following aspects:

1. Python

Python is probably the most widely utilized general-purpose programming language today. Developed to improve the readability of codes, the language has quickly managed to become a preferred choice. Python, as a programming language, has been built using an object-oriented approach to help programmers to write clean, efficient, and logical codes for different types of development activities. In addition to modern web and mobile app development projects, Python is also a prime solution for building data analytics, ML, and other data-driven services. It is an extremely versatile language capable of supporting essential tasks to define the logic of applications.

2. Java

Java should also be considered one of the primary languages to build a career as a back-end integrations engineer. One of the most widely utilized programming languages in use today, Java is a general-purpose language capable of supporting several niches. It is a preferred choice of developers as it helps to write and run codes anywhere irrespective of the architecture of the system. It is also a language that offers write-once and run-anywhere models; this helps developers to compile codes on any platform that supports the Java Runtime Environment. So, if you plan to define your career as a back-end integrations engineer, deep Java development knowledge would be really helpful.

3. RESTful APIs

REST, short for representational state transfer, is a set of definitions and protocols used for building and integrating applications. RESTful APIs are a perfect choice for software development of various niches and can also help to make solutions scalable. As a back-end integrations engineer, the ability to take charge of integration processes and draft thorough documentation can be one of the defining traits. For which, keep developing a thorough understanding of working with API-related tasks like - developing, modifying, and maintaining. You should also be able to understand project requirements to implement the required logic.

4. Versioning tools

Most tech firms today build and maintain software applications using small and scalable modules of code. This allows teams to maintain the stability of applications, even while configuring upgrades and new features. To work efficiently in such models, version control systems offer deep insight. Developers can use these tools to keep track of modifications made to codes during the development process. It not only helps developers to stay updated with the codebase but helps to quickly switch to a stable version in case of emergencies. So, having familiarity or experience of working with such tools will help you become a more efficient back-end integrations engineer.

5. Interpersonal skills

Working in the modern software development industry requires a lot more than technical proficiency. Developers today need to undertake various responsibilities outside their core competencies. They often also need to collaborate with different cross-functional teams and interact with clients to produce high-quality software. For which, interpersonal skills play a huge part in today’s agile work culture. Developers need to actively interact and share their opinion from time to time to keep the chain of information flowing. So to find success working as a back-end integrations engineer, brushing up on language skills and openness to collaborate has become essential.

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How to get hired as a remote back-end integrations engineer?

Companies today prefer to work with professionals with a deep understanding of important technologies. For which constantly upgrading personal tech stack and developing knowledge of various domains has become essential. In addition to core technologies required for backend development, developers also need to have a clear idea about user-preferences. This allows developers to build entire applications and front-ends drawing inspiration from preferred features. The primary objective of any back-end integrations engineer is to build efficient solutions that offer class-apart user experience using intuitive interfaces.

Turing has quickly become the premier platform for taking careers forward working as a remote back-end integrations engineer. We provide developers opportunities to work on era-defining projects and business problems using state of the art technologies. Join the fastest growing network of the top developers around the globe to get hired as a full-time and long-term remote back-end integrations engineer developer with the best pay packages.

Why become a back-end integrations engineer developer at Turing?

Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top US firms from the comfort of your home.

Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their back-end integrations engineer?

Every back-end integrations engineer at Turing can set their own pricing. Turing, on the other hand, will recommend a salary to the back-end integrations engineer for which we are confident of finding a fruitful and long-term opportunity for you. Our salary recommendations are based on an analysis of market conditions as well as customer demand.

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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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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