Go AI Jobs

Discover the latest remote and onsite Go AI roles across top active AI companies. Updated hourly.

Check out 128 new Go AI roles opportunities posted on The Homebase

Expansion Account Executive

New
Top rated
Arize AI
Full-time
Full-time
Posted

Debug and fix issues in the platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.

Undisclosed

()

Buenos Aires, Argentina
Maybe global
Remote
Python
Go
JavaScript
TypeScript
OpenAI API

Engineering Leader

New
Top rated
Ema
Full-time
Full-time
Posted

As an Engineering Leader at Ema, you will build and lead a high-performance engineering organization by recruiting, hiring, and developing senior engineers across multiple sub-teams including cloud infrastructure, data platform, ML operations, and developer experience. You will establish engineering standards, a code review culture, on-call expectations, and promote a bias-toward-shipping mentality balanced with production rigor. You will coach and grow senior and staff engineers into technical leaders and manage engineering managers as the organization scales. Your responsibilities include setting the 6–18 month platform roadmap in partnership with engineering teams, making critical architectural decisions such as build versus buy and migration strategies, and driving cross-functional alignment with product, ML/AI research, and go-to-market teams. You will own production health for all platform services, including incident response, postmortems, SLO tracking, and capacity planning. Additionally, you will establish and refine engineering practices to maintain fast shipping without compromising reliability, and participate in executive-level reviews related to infrastructure spend, system health, and engineering velocity.

Undisclosed

()

Bengaluru, India
Maybe global
Onsite
Go
Python
Kubernetes
AWS
GCP

Senior Python Systems Developer - Functional Testing Project

New
Top rated
Mindrift
Part-time
Full-time
Posted

Create functional black box tests for large codebases in various source languages, create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms, monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards, and leverage LLMs such as Roo Code and Claude to accelerate development cycles, automate repetitive tasks, and improve overall code quality.

$50 / hour
Undisclosed
HOUR

(USD)

Germany
Maybe global
Remote
Python
Docker
Linux
Go
C++

Engineering Manager, Go - Assist & Chat

New
Top rated
Grammarly
Full-time
Full-time
Posted

Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts, including development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.

$103,000 – $174,000
Undisclosed
YEAR

(USD)

San Francisco
Maybe global
Onsite
Go
Kubernetes
Google Cloud
Docker
CI/CD

Compliance Program Manager

New
Top rated
Grammarly
Full-time
Full-time
Posted

Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage, including cost per feature, token patterns, and latency. Create systems that connect user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.

$103,000 – $174,000
Undisclosed
YEAR

(USD)

Ukraine
Maybe global
Remote
Go
Kubernetes
Google Cloud
MLOps
Observability

Enterprise Account Executive (New York City)

New
Top rated
Arize AI
Full-time
Full-time
Posted

Debug and fix issues in the platform and ship PRs with fixes. Build internal tools and copilots powered by generative AI to enhance team capabilities. Rapidly prototype proof-of-concepts for customer use cases. Work collaboratively across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.

Undisclosed

()

New York
Maybe global
Remote
Python
Go
OpenAI API
LangChain
JavaScript

Senior Engineer, Internal tools

New
Top rated
Bjak
Full-time
Full-time
Posted

The Senior Engineer on the internal tools team is responsible for building and maintaining internal platforms and tools used by various departments such as People, Finance, Ops, Sales, and Engineering. The role involves owning features end-to-end, including requirements gathering, architecture, implementation, testing, deployment, and monitoring. The engineer is expected to write clean, well-tested, production-grade code and build API-first integrations to connect multiple business systems like HRIS, CRM, finance platforms, and developer tools. Responsibilities include designing for reliability, performance, and scalability, eliminating data silos by creating clean data pipelines, and owning services in production with monitoring, alerting, incident response, and post-mortems. The role also involves building AI/LLM-powered features to automate internal workflows, moving prototypes to production, and staying updated on emerging AI technologies. Collaboration includes working directly with business stakeholders to translate pain points into technical solutions, mentoring junior engineers, conducting code and design reviews, influencing technical direction, proposing architectural improvements, and driving best practices across the team.

Undisclosed

()

New York, United States
Maybe global
Remote
Python
Go
TypeScript
Docker
Kubernetes

Senior Brand Events Manager

New
Top rated
Grammarly
Full-time
Full-time
Posted

Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage: cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.

$103,000 – $174,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Onsite
Go
Kubernetes
Google Cloud
OpenAI API
MLOps

Intern, Software Engineer - Platform

New
Top rated
Haydenai
Intern
Full-time
Posted

As a Platform Engineering Intern at Hayden AI, you will take ownership of a real project and see it through to completion, build and ship features with support from senior engineers, write clean and scalable code, test your work and iterate quickly, be involved in design discussions, deployment, collaborate with engineers in code reviews and team discussions, participate in standups, sprint planning, and retrospectives, support the team on ad hoc engineering tasks, help improve performance, reliability, or usability where needed, and ask questions, seek feedback, and apply it quickly. The work spans building foundational systems that power the product, including infrastructure, services, and data pipelines to ensure Perception algorithms run reliably across edge devices and cloud environments. Projects may include GPS data analysis, training deep learning models, creating AI datasets, lidar/camera data tooling, test cases for end-to-end system performance, developing cloud services in the event processing pipeline, and adding pages or user flows to the Portal web application.

$45 – $45 / hour
Undisclosed
HOUR

(USD)

San Francisco, United States
Maybe global
Hybrid
Python
Go
Docker
Kubernetes
AWS

Offensive Security Engineer

New
Top rated
Replit
Full-time
Full-time
Posted

Lead advanced whitebox penetration testing engagements with full access to source code, identifying systemic weaknesses, logic flaws, and architectural gaps. Simulate sophisticated adversary tactics across web applications, APIs, and containerized infrastructure such as Kubernetes and Docker. Perform offensive testing on AI-enabled systems, focusing on prompt injection, data leakage, and abuse of AI-driven components. Identify, exploit, and demonstrate realistic business risks by chaining vulnerabilities through various trust boundaries. Build offensive tooling and AI-assisted testing tools to automate bug discovery while maintaining deep manual testing. Collaborate with product teams and security architects to explain root causes, influence design guardrails, and triage high-priority findings from the Bug Bounty program.

$188,000 – $313,000
Undisclosed
YEAR

(USD)

Foster City, United States
Maybe global
Hybrid
Go
Python
TypeScript
Docker
Kubernetes

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[{"question":"What are Go AI jobs?","answer":"Go AI jobs involve developing the infrastructure and systems that power AI applications. These positions focus on building high-performance backends, data processing pipelines, real-time AI services, and scalable frameworks that handle LLM requests. Golang is particularly valued for its concurrency capabilities when creating AI-powered chatbots, recommendation engines, computer vision systems, and edge AI applications."},{"question":"What roles commonly require Go skills?","answer":"Backend developers for AI applications frequently need Go skills, as do engineers working on production AI system deployment and cloud infrastructure. The language is especially valuable in roles involving real-time processing in eCommerce, banking, healthcare, and customer service platforms. Engineers building voice transcription systems, IoT applications, robotics, and networked services also commonly require Go expertise."},{"question":"What skills are typically required alongside Go?","answer":"Alongside Go, employers typically seek proficiency in high-performance computing, multithreading, concurrent programming, and memory-efficient data handling. Experience with tools like GoCV for computer vision, Fuego for fuzzy logic, and Gobot for IoT is valuable. Knowledge of vector databases, Google Cloud Profiler, and cross-platform deployment is often required, as is the ability to integrate with Python codebases for AI model training."},{"question":"What experience level do Go AI jobs usually require?","answer":"The research doesn't specifically address experience levels for Go AI jobs. Typically, these positions require strong knowledge of concurrent programming, memory management, and integration with AI services. Since these roles often involve production systems and scalable infrastructure, mid to senior-level experience with both Go and AI concepts is commonly expected, though requirements vary by company and specific position."},{"question":"What is the salary range for Go AI jobs?","answer":"The provided research doesn't contain specific salary information for Go AI jobs. Compensation typically varies based on factors like location, company size, experience level, and specific technical requirements. Go developers working on AI applications often command competitive salaries due to the specialized intersection of high-performance programming and artificial intelligence expertise."},{"question":"Are Go AI jobs in demand?","answer":"Yes, the demand for Golang in AI application development is increasing. This growth is driven by performance requirements in computer vision, real-time systems, and production AI deployments. Startups, enterprises, and cloud providers are adopting Go for building scalable, secure AI applications. The language is particularly sought after for customer service platforms handling millions of LLM requests and real-time transcription services."},{"question":"What is the difference between Go and Java in AI roles?","answer":"The research doesn't directly compare Go and Java for AI roles. However, Go typically excels in building high-performance, concurrent systems with efficient memory usage and faster startup times—ideal for AI service deployment and orchestration. Java offers robust enterprise features and extensive libraries, but may have higher memory requirements. In AI contexts, Go is often preferred for microservices, real-time processing, and lightweight applications where performance is critical."}]