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Remote Go/Kafka developer jobs

We, at Turing, are looking for experienced remote Go/Kafka developers who can ensure optimum performance, high availability, and stability of software solutions. Here’s your opportunity to work with elite U.S. companies and collaborate with top professionals across the globe.

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Job description

Job responsibilities

  • Write scalable, robust, efficient, testable, and easily maintainable code
  • Translate user requirements into stable, and high-performance software
  • Execute code and unit testing for complex scope modules, and projects
  • Analyze and maintain existing requirements and implement them into solutions
  • Design highly scalable, testable code
  • Conducting performance tests, troubleshooting issues, and monitoring the performance of the application

Minimum requirements

  • Bachelor’s/Master’s degree in Computer Science or IT (or equivalent experience)
  • 3+ years of experience working as a Go/Kafka developer (rare exceptions for highly skilled developers)
  • Proficiency in Kafka, Golang, and Big Data.
  • Good understanding of common Goroutine and channel patterns
  • Experience working with dependency management tools and code generation tools
  • Experience working with Kafka brokers, zookeepers, KSQL, KStream, and Kafka Control center.
  • Expertise with AvroConverters, JsonConverters, and StringConverters
  • Experience with popular Go web frameworks like Revel, and router packages
  • Experience working with SQL/NoSQL databases
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones
  • Fluency in English to communicate effectively with engineering leaders

Preferred skills

  • Excellent knowledge of in-memory applications, database design, data integration.
  • Knowledge of CI/CD, and containerization technologies such as Docker, Kubernetes, etc.
  • Experience in code versioning tools like Git, SVN, Mercurial, etc.
  • Experience with cloud infrastructures like AWS, Azure, and GCP

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How to become a Go/Kafka developer?

Go/Kafka is rapidly displacing Python. We'll explain why you should use Golang and Kafka and how to become a Go/Kafka developer in this part. Before making a final selection, it is critical to have a deeper understanding of the language.

Because of its many advantages, Golang will be the reference language for software development. Python is being phased out in favor of Go among developers, and it is also becoming the preferred language among customers.

Apache Kafka is a stream-processing framework making use of a software bus. It is a Scala and Java-based open-source development platform created by the Apache Software Foundation. The project aims to provide a single, high-throughput, low-latency platform for real-time data flows. Kafka Connect is a platform for users to connect to external systems (for data import/export) and includes Kafka Streams, a Java stream processing framework. Kafka employs an efficient binary TCP-based protocol that depends on a "message set" concept that naturally groups messages together to decrease network round trip time. This is how Kafka transforms a stream of random message writes into linear writes. Which in turn results in “bigger network packets, longer sequential disc operations, and contiguous memory blocks."
So, if you are confused about applying for remote Go/Kafka developer jobs, just go ahead. Opportunities are waiting for you.

What is the scope of Go/Kafka development?

Go is one of the most recent additions to the current programming language landscape. It bills itself as "an open-source programming language that enables creating simple, reliable, and efficient software simple, reliable, and efficient." It also allows programmers to design reliable and efficient software that is succinct, simple, and secure. Go, being a contemporary programming language, may assist you in quickly developing cross-platform and multi-element products. Because Go is simple to program and test, there are more Golang remote developer jobs available.

In this digital era, the necessity to collect data and analyze it in real-time has virtually become a must. When it comes to Kafka stream processing, Apache projects like Apache Kafka, Storm, and Spark remain prominent.

Engineers have begun to integrate Kafka with Storm and Spark over time. Many businesses are quickly adopting Apache Kafka. That is to say, Kafka’s employment and Kafka’s careers are on the rise.

LinkedIn has implemented one of the largest Kafka clusters. "Back in 2011, it was absorbing more than 1 billion events each day," according to the research. It recently announced daily absorption rates of 1 trillion texts."

Do these references compel you to apply for remote Go/Kafka developer jobs? Let's delve a little deeper into the roles and responsibilities to learn more.

What are the roles and responsibilities of a Go/Kafka developer?

The employment function of a Golang developer is frequently decided by the project type, required upgrades, or management. They are primarily responsible for developing a high-quality, error-free technology infrastructure, establishing and maintaining an effective operational environment with a 99.99 percent uptime, and delivering high-quality, prompt, cost-effective, and reliable technology services to provide customers with the best impossible experience possible.

After landing remote Go/Kafka developer jobs, a developer's primary tasks are as follows:

  • Building and Research: Many Golang engineers, despite their expertise in testing and development, are forced to create solutions without a roadmap. You are a part of the bigger picture, and you must be ready to contribute significantly to the creation of creative solutions. For Golang programmers, this means creating software that runs on a variety of platforms.
  • Creating Software Solutions: A Golang developer's job is to use the essential tools to produce efficient, scalable, and modular software. Your job includes creating and coding backend components as well as connecting apps to other online services.
  • Writing Codes: A Golang developer's primary purpose is to produce efficient code for the complete software architecture. Most Golang programmers work in teams or cooperate with other programmers, thus they only work on specific software solutions or product components. As a result, understanding the deployment protocol is a crucial part of a Golang developer's professional obligations.

Developers that work with Kafka have a mix of technical, communication, and business experience. Let's take a look at the tasks and roles of a Kafka developer.

  • Participate as an individual contributor and as part of a team in the creation, improvement, and maintenance of web applications.
  • Within the production environment, lead the detection, isolation, resolution, and communication of problems.
  • Using Apache/Confluent Kafka, design and propose the optimum technique for data migration to/from various sources.

How to become a Go/Kafka developer?

To become a Go/Kafka developer, you'll need a lot of practice, commitment, and time. Taking college-level Go/Kafka programming courses is the most apparent method to get started. Computer science is the most popular program for college graduates who want to become developers. It's worth noting, though, that being a Go/Kafka developer does not necessitate a computer science degree or diploma. It's simple to get a remote Go/Kafka developer job if you're familiar with Go/Kafka and its tech stacks. Choose a software solution to work on, then practice as much as possible to become proficient at applying it to various jobs and coding projects.

Understanding how to use codes to apply your technical knowledge in real-world assignments and tasks tests your talents while also allowing you to learn as you go. This is crucial if you want to construct a portfolio as a Go/Kafka developer that you can show to potential employers.

Let's take a look at the abilities and procedures you'll need to become a good Go/Kafka developer:

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Skills required to become a Go/Kafka developer

The first step is to begin learning the necessary abilities for high-paying Go/Kafka developer jobs. Let's have a look at everything you'll need to know to become a Go/Kafka developer.

1. Go Libraries

Go Kit, GORM, Gen, and CLI are the most widely used Go libraries. Working with Go will be significantly easier if you use decent libraries and packages. Each has its own distinct qualities, so picking one that best fits your objectives and working on it is a smart idea. If you learn how to use them for app development projects, impressing recruiters for remote Go/Kafka developer jobs will be a cakewalk for you.

2. Error handling

It is a vital component of writing code that is strong, dependable, and maintainable. Self-programming might assist you in adapting to new surroundings. Error handling is an important aspect of developing strong, stable, and trustworthy code when writing libraries or packages for people to utilize.

3. JSON

The JSON file is another fundamental and probably more important component in Golang. You must produce JSON files as a Golang developer. Simply said, it organizes and maintains package data and dependencies, as well as the project's script. If you ever need to verify what packages or dependencies to utilize in the application, you can quickly access this file and review the details. Therefore, be familiar with JSON to land the best remote Go/Kafka developer jobs.

4. Kubernetes or Docker

Docker makes it easy to "create" containers, but Kubernetes allows for real-time container management. Docker is used to package and ship software. Use Kubernetes to launch and grow your app. Startups and small enterprises with fewer containers can usually manage them without Kubernetes, but as their infrastructure demands expand, so will the number of containers, making administration increasingly difficult. This is where Kubernetes comes into play.

When used together, Docker and Kubernetes are digital transformation enablers and technologies for modern cloud architecture. Using both has become the new industry norm for faster application deployments and releases. While designing your stack, it's critical to understand the high-level differences between Docker and Kubernetes.

5. AWS and Azure

Amazon Web Services (AWS) is an Amazon cloud service platform that provides computing, storage, delivery, and other capabilities to help organizations expand and prosper. These domains might be used as services on the cloud platform, which could be used to construct and deploy a variety of apps.

Microsoft Azure is a cloud service platform created by Microsoft that provides services in a range of disciplines, such as compute, storage, database, networking, developer tools, and other capabilities that help organizations expand and thrive. PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as a service) are three Azure services that developers and software employees use to create, deploy, and manage cloud services and applications.

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How to get remote Go/Kafka developer jobs?

Athletes have a lot in common with Go/Kafka developers. They must practice successfully and on a regular basis in order to be the greatest in their field. They should also put in enough effort to improve their talents over time. When practicing, Go/Kafka developers should enlist the assistance of a successful Go/Kafka expert, as well as the use of more effective, practice strategies. Knowing how much to practice as a Go/Kafka developer is critical. So enlist the support of a Go/Kafka developer and keep an eye out for burnout signals!

Turing provides the top remote Go/Kafka developer jobs to assist you to reach your professional goals as a Go/Kafka developer. We allow you to work on challenging technical and business challenges utilizing cutting-edge technology, allowing you to swiftly enhance your abilities. Get full-time, long-term remote Go/Kafka developer employment with greater income and professional progress by joining a network of the world's greatest Go/Kafka developers.

Why become a Go/Kafka developer at Turing?

Career growth
Elite US Go/Kafka developer jobs
Exclusive developer community
Once you join Turing, you'll never have to apply for other remote Go/Kafka developer jobs
Work from the comfort of your home
Great compensation

How much does Turing pay their Go/Kafka developers?

Every Go/Kafka developer may set their own pace at Turing. Turing, on the other hand, will suggest a salary to the Go/Kafka developer at which we are certain we will be able to offer you a rewarding and long-term job. Our compensation suggestions are based on our research into market conditions as well as consumer 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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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.

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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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