Turing

Remote senior DevOps/back-end engineer jobs with U.S. companies

We, at Turing, are looking for talented remote senior DevOps/back-end engineers who will be responsible for deploying product updates, identifying production issues, and implementing integrations to meet client requirements. Here's the best chance to collaborate with top industry leaders while working with top Silicon Valley companies.

Find remote software jobs with hundreds of Turing clients

Job description

Job responsibilities

  • Collaborate with team members to ideate engineering approaches and solutions
  • Conduct research, recognize scope options, present & assess trade-offs to make informed decisions
  • Build back-end components and RESTful APIs using Python, NodeJS, AWS services, and databases
  • Peer review code to analyze, organize and share in-depth feedback to improve applications dynamically
  • Configure and maintain repeatable infrastructure-as-code and CI/CD pipelines to deploy code
  • Produce and maintain technical architecture diagrams and documentation
  • Assist in internal non-conformance management solution portfolio across the complete application lifecycle
  • Ensure reliable operations and support ticket handling
  • Take ownership of evaluating and improving software delivery processes
  • Collaborate with cross-functional teams to improve engineering tools, technology stack, and application performance

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • 5+ years of experience in software engineering and DevOps (rare exceptions for highly skilled developers)
  • Excellent knowledge of Python
  • Strong grasp of test automation and test-driven development
  • Knowledge of relational, graph, or NoSQL databases including PostgreSQL, MSSQL, MySQL, Oracle, MongoDB, Cassandra, DynamoDB, etc.
  • Proficient with OOP language including Python
  • Strong knowledge of Linux systems like Ubuntu
  • Expertise in problem-solving with scripting languages, like Ruby or Python, in a Linux environment
  • Experience using identity and access management solutions for user authentication and authorization
  • Experience with Git or comparable distributed version control system
  • Hands-on knowledge of CI/CD, RESTful API, and JSON fundamentals
  • Good understanding of container systems, like Docker and Kubernetes
  • 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

  • Knowledge of cloud hosting with Microsoft Azure, Alibaba Cloud, etc.
  • Familiarity with automation/monitoring tools like Jenkins, Ansible, Grafana, or any IaaS provider, like Azure or AWS
  • Basic knowledge of GDAL
  • Knowledge of REST API development and implementation
  • Understanding of ETL, entity resolution, and processing large amounts of data
  • Knowledge of cybersecurity and risk management
  • Clear idea of Agile delivery methods, such as Scrum
  • Excellent organizational, communication, and leadership skills
  • Great technical, analytical, and problem-solving skills

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How to become a Senior DevOps/Backend Engineer?

A web app's backend is its server-side functionality. That is where all of the inner workings of web applications occur, as well as where backend engineers work. The role of a Senior DevOps/Backend Engineer is to build code in programming languages that allow web applications to function properly. Senior DevOps engineers also referred to as senior developers, manage teams of junior software developers. They must have extensive experience in development, operations, and full-stack deployments.

The code created by these engineers is executed by the webserver. In addition to writing back-end code, such engineers are responsible for developing APIs that are used by mobile versions of such internet apps. Senior DevOps/Backend Engineer is all about connecting and automating processes, and Senior DevOps/Backend experts are critical in connecting code, application maintenance, and application management. All of these roles demand a solid understanding not only of development life cycles, but also of DevOps culture, including philosophy, methodology, and tools.

What is the scope for senior DevOps/Backend software engineers?

Senior DevOps/Backend software engineers are in high demand as the number of technology-based businesses grows. Because accessibility is so important these days, the number of remote web backend tasks is growing. Businesses rely on backend software professionals to ensure the scalability and security of their programmes.

Artificial intelligence and machine learning developments have paved the way for a new breed of entrepreneurs. These entrepreneurs are doing everything they can to take advantage of the demand-supply imbalance. Back-end developers will have more opportunities as more products are developed. But, before you apply for remote lead back-end engineer jobs, read on for additional information in the areas below. As a result, as more goods are generated, the demand for backend software engineers will increase.

What are the roles and responsibilities of a senior DevOps/back-end engineer?

Some of the most crucial tasks after winning remote lead back-end engineer positions are as follows:

  • Lead the development of a high-performance, scalable, responsive, and reliable back-end infrastructure.
  • Participate in the processes of site architecture, feature components, development, SDLC tools, and system design.
  • Product requirements and technical designs must be converted into well-structured, clean, scalable, and robust code.
  • Examine new technology or processes for ways to improve architecture, user experience, and the overall development process.
  • Participate in code reviews, listen to comments, and share what you've learned with other team members and stakeholders.
  • Collaborate with cross-functional teams to launch new growth initiatives.
  • Recognize performance bottlenecks and create and deploy appropriate solutions.
  • Supervising normal maintenance operations and performing diagnostic testing.
  • Processes are documented, and key performance indicators are monitored.
  • Best practices for network management and cybersecurity are followed.

How to become Senior DevOps/back-end engineer?

Although remote lead back-end engineer jobs need a high degree of competence and expertise, anyone with a genuine interest in the field—and the ability to accomplish at least some of the responsibilities described above for a lead back-end engineer—is eligible to apply.

There are several ways to learn the skills needed to become a lead back-end engineer. You can begin by attending college, which is the most frequent option. When it comes to entering the field, a computer science degree will offer you with a solid foundation and credentials. College is expensive, and the time it takes to complete it is a disadvantage. Furthermore, if you did not receive strong grades in high school, you may be unable to enroll in a college that will help you discover lead back-end engineer jobs.

Another option is to join a boot camp programme. The focus will be on teaching you the languages you'll need to apply for remote lead back-end engineer jobs in person or online. This could be a less expensive and time-consuming choice than a three- or four-year degree.

You can be confident that no matter the path you take to become a remote lead back-end engineer, you'll have a bright future and plenty of chances in remote lead back-end engineer employment ahead of you.

Interested in remote senior DevOps/back-end developer jobs?

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Skills required to become senior DevOps/back-end developer

The first step toward landing high-paying lead back-end engineer positions is to get the relevant abilities. Let's take a closer look at each technical talent required to become a lead back-end engineer.

1. Python

Python is an Object-Oriented Programming (OOP) language since its design is built around the concept of classes and objects. Python is utilized in the backends of businesses like Spotify, Uber, Instagram, and Dropbox. Because of its simplicity of use with frameworks and excellent data visualization, it is one of the most popular programming languages. Its grammar is straightforward, and the language is similarly straightforward to learn. As a result, newcomers are encouraged to learn the language as soon as possible. Strong Python skills are one method to get a position as a remote lead back-end engineer.

2. PHP

PHP (Hypertext Preprocessor): PHP is a free and open-source programming language that may be used to produce dynamic web pages and boost application performance. Unlike Python, PHP is used on the server to read scripts or programming instructions. PHP is used in the backends of businesses such as Hootsuite, Viber, and Facebook. Collecting and securely storing user information is one of PHP's most commonly utilized functions. It is inexpensive because of its built-in MySQL support and compatibility with the majority of web hosting providers. PHP-fluent back-end professionals are in high demand due to their versatility and expertise in web development. If you want to get remote back-end engineer jobs, you must be able to code in PHP.

3. Knowledge of numerous DevOps tools and technologies:

DevOps methods are implemented in stages, each with its own set of tools to help the process. The following are the main stages:

  • Source code management: Software developers generate and alter code on a regular basis. To store code, integrate new code into old code, manage code versions, and so on, source code management software is utilized. It also makes working on source code easier for team members. Git, GitHub, and Gitlab are the most common tools for this.
  • Configuration management is the process of tracking software and operating system configurations. It also aids in the administration of thousands of server configurations.
  • Continuous integration (CI) is the process of automating the merging of code from several developers into a single piece of software. Jenkins and Bamboo are the most popular Continuous Integration tools.
  • Continuous testing is a strategy for reducing the time it takes to receive feedback following a code test. In the development environment, automation testing tools are used to test the code. Selenium, Test Complete, and Testing Whiz are the most popular Continuous Testing tools.
  • Continuous monitoring is used to maintain track of things like application performance, downtime, and error logs. Commonly used tools include Nagios, Zabbix, Splunk, and others.
  • Containerization is the virtualization of an operating system in such a way that numerous containers running different programmes can share the same operating system and resources. In contrast, the traditional method of hardware virtualization includes sharing the system hardware among numerous virtual computers. Docker, Kubernetes, and vagrant are among the top containerization providers.

4. Continuous integration and continuous delivery

Continuous integration and continuous delivery (CI/CD) are at the heart of DevOps. It is the continuous integration of code from several developers, testing it, and finally delivering the successful code to production. Deploying to production will mostly entail the creation of new containers, which will be automated once more through the use of scripts.

5. Database management systems (DBMS)

Database management systems (DBMS) should be familiar to all back-end developers. The ability of a back-end developer is determined by his or her ability to explore and manage databases. So, if you want to land the greatest remote lead back-end engineer jobs, you should learn DBMS.

6. SQL and NoSQL databases

SQL and NoSQL databases are the two types of databases that are in use. SQL allows database designers to create new tables and stored procedures. SQL is necessary to navigate a relational database and make insert, remove, or file requests. NoSQL stores data in a different way than relational databases, but it may also store relational data. There is no need to prepare data prior to using NoSQL.

Interested in remote senior DevOps/back-end developer jobs?

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Apply now

How to get remote senior DevOps/back-end engineer jobs?

We've seen the skills needed for remote lead back-end engineer positions. The most important thing to remember when training is to give it your all. New technology breakthroughs transform sectors on a daily basis. More people will enter the field as it becomes more popular, increasing your competition. If you keep up with current industry developments, it won't be tough to improve your career in back-end development.

Turing has the greatest remote lead back-end engineer jobs to help you reach your lead back-end engineer goals. You'll also have the opportunity to hone your skills by working on complex technological problems alongside other bright engineers.
Join a global network of the greatest back-end specialists to locate full-time, long-term remote lead back-end engineer jobs that pay more and provide opportunities for advancement.

Why become a Senior DevOps/Backend engineer at Turing?

Elite US jobs
Career growth
Exclusive engineer community
Once you join Turing, you'll never have to apply for other senior DevOps/Backend engineer jobs.
Work from the comfort of your home
Great compensation

How much does Turing pay their Senior DevOps/Backend engineer?

Every lead back-end engineer at Turing has the ability to set their own rate. Turing, on the other hand, will recommend a pay at which we believe we can locate a fruitful and long-term opportunity to advance your lead back-end engineer career. Our recommendations are based on an examination of current market conditions as well as client desire.

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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