Senior AI Native Engineer (Go)

We are looking for a senior AI Native Engineer (Go) to develop and maintain an enterprise Service Order Management platform for a major network infrastructure provider. You will work on Go services, Temporal workflows and API and messaging integrations running on AWS.
The role combines hands-on software engineering with AI-native, specification-driven development. You guide approved AI tools, validate their output and take ownership of changes through testing, release support and production troubleshooting.

Technology Environment

• Go microservices, Temporal and Temporal Cloud for durable workflow orchestration.
• AWS and Amazon Aurora, SQL persistence and Go Migrate for schema migrations.
• JSON APIs, TM Forum Open APIs and Apache Kafka integrations.
• GitHub, pull-request reviews, automated checks and repository-defined AI skills.
• Component and workflow tests, plus integration tests with programmable downstream stubs.

Responsibilities

• Clarify requirements with architects and client teams; turn them into reviewed specifications and testable acceptance criteria.
• Develop and maintain Go services, Temporal workflows and reusable platform components using established engineering conventions.
• Implement API and Kafka integrations, including payload validation, asynchronous completion, retries and failure handling.
• Review AI-generated specifications, code, tests and schema changes for correctness, maintainability, security and architectural fit.
• Direct AI tools through refinement cycles, challenge incorrect assumptions and debug or rewrite generated code when needed.
• Write and validate automated tests covering component behavior, workflow transitions, integration failures and regressions.
• Diagnose issues across services, workflows, integrations and databases using code, logs, metrics and execution history.
• Assess shared-component changes and coordinate releases, migrations and rollback readiness with SREs and platform owners.
• Keep specifications and documentation aligned with implementation; contribute to knowledge transfer, code reviews and mentoring.

Required Experience

• Strong professional Go experience, including concurrency, error handling and maintainable service design.
• Experience developing distributed services, APIs and asynchronous or event-driven applications.
• Understanding of workflow state, retries, timeouts, idempotency and failure recovery.
• Practical SQL and relational database experience, including schema changes and migrations.
• Automated testing experience, including component and integration tests with mocks or stubs.
• Strong debugging and code-review skills; confidence navigating an existing codebase and assessing the impact of changes.
• Experience with cloud environments, Git, pull requests and automated build and test checks.
• Practical ability to direct AI coding tools, identify flawed output and verify changes independently; readiness to use approved tools daily.
• Clear communication and engineering judgment when resolving incomplete requirements with architects and client teams.

AI Native Engineering Workflow

Work starts with a clear requirement and a reviewed specification. Engineers guide AI agents using repository instructions and approved building blocks, then inspect the implementation and test results. You remain accountable for correctness and readiness before merge and deployment.
You should be able to explain the generated code, find missing edge cases and test whether the implementation meets the intended behavior. Experience with a specific AI product is not required; tools and data handling follow the client’s approved process.

Preferred Experience

• Temporal or another durable workflow platform, including workflows, activities and workers.
• AWS, Amazon Aurora and Kafka in production.
• Specification-driven development, reusable agent instructions and AI-assisted test generation.
• TM Forum Open APIs, telecom service orchestration or ownership of an existing platform.

Working Hours

Full-time remote work with regular overlap with a U.S.-based client team, including availability until at least 7:00 PM CET/CEST on regular working days. Occasional later meetings may be needed for knowledge transfer, releases or production issues.

Why Work With Us?

Our Culture

• Open communication and a focus on psychological safety
• Recognition of achievements and individual contributions
• Collaboration across multicultural and distributed teams
• Less bureaucracy and greater focus on outcomes
• Opportunity to work with modern AI-assisted engineering practices
• Direct involvement in technically challenging enterprise platforms

Hiring Process

1. Intro Call
2. Technical Interview
3. Manager Interview
4. Client Technical \ Manager Interview
5. Pre-offer Stage + Reference Check, if requested
6. Official Offer