Asks for

The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Relevant backgrounds include backend, platform, infrastructure, and developer experience engineering. Experience with internal platforms, developer tooling, distributed systems, or production AI systems is a plus.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Relevant backgrounds include backend, platform, infrastructure, and developer experience engineering. Experience with internal platforms, developer tooling, distributed systems, or production AI systems is a plus.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“This is not an entry-level AI role. You need a strong understanding of software architecture, maintainability, infrastructure, and production operations. Prior LLM experience is useful but not essential; the ability to evaluate the technology critically and apply it with engineering discipline matters more.”
The ad says“Relevant backgrounds include backend, platform, infrastructure, and developer experience engineering. Experience with internal platforms, developer tooling, distributed systems, or production AI systems is a plus.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“This is not an entry-level AI role. You need a strong understanding of software architecture, maintainability, infrastructure, and production operations. Prior LLM experience is useful but not essential; the ability to evaluate the technology critically and apply it with engineering discipline matters more.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“Relevant backgrounds include backend, platform, infrastructure, and developer experience engineering. Experience with internal platforms, developer tooling, distributed systems, or production AI systems is a plus.”
The ad says“This is not an entry-level AI role. You need a strong understanding of software architecture, maintainability, infrastructure, and production operations. Prior LLM experience is useful but not essential; the ability to evaluate the technology critically and apply it with engineering discipline matters more.”
The ad says“Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.”
The ad says“This is not an entry-level AI role. You need a strong understanding of software architecture, maintainability, infrastructure, and production operations. Prior LLM experience is useful but not essential; the ability to evaluate the technology critically and apply it with engineering discipline matters more.”

Company Description

Streem Energy builds a SaaS platform helping energy players operate renewable assets across Europe: producers, aggregators and suppliers.

Our software sits at the intersection of renewable energy generation, European power markets, and complex operational workflows. We combine strong engineering, data/AI, and deep energy-market expertise to turn real-world signals and constraints into actionable decisions.

Job Description

Software engineering is entering a period of fundamental change. LLMs are reshaping how software is designed, implemented, reviewed, and maintained, but the practices and systems needed to use them reliably are still being defined.

Streem engineers already use tools such as OpenAI Codex. Our ambition is to go much further: to define how AI should be integrated into our engineering organization and turn that vision into systems with an immediate, measurable impact on how our teams build software.

This is fundamentally a software engineering challenge. LLMs need the right context, data, documentation, constraints, and feedback loops to produce code that fits our architecture and engineering standards.

That is the purpose of the Rocket team.

The Rocket Team

Rocket builds the internal platform that enables Streem’s Product Builders to use AI throughout the software development lifecycle.

We are not building a generic coding assistant. We are creating systems adapted to Streem’s repositories, architecture, infrastructure, data, and ways of working.

This requires selecting and structuring the right context, connecting models to internal resources, and rigorously evaluating their output. Our standard is not code that simply compiles or works in a demonstration, but maintainable, tested, production-ready code that Streem engineers can trust.

Qualifications

The Role

You will work directly with the Head of Engineering in a small team of experienced engineers.

This is a demanding role combining strong software engineering fundamentals with a deep understanding of how Streem’s Product Builders work. Before automating engineering workflows, you will need to understand our teams, codebases, systems, and architectural decisions—then turn that knowledge into reliable tools and infrastructure.

The field is evolving quickly, and many promising prototypes fail in production. You will need to experiment pragmatically, make sound decisions with incomplete information, and take ownership of maintainability, security, observability, and reliability.

What You’ll Do

Understand how Streem’s teams design, build, review, deploy, and operate software
Provide LLMs with the right code, documentation, data, and engineering context
Build AI workflows that analyze repositories, implement changes, run checks, and propose pull requests
Integrate GitHub, CI/CD, observability, and internal systems
Develop evaluation and feedback systems to improve the quality of generated code
Build secure, reliable developer tools used daily by Product Builders
Help resolve critical application issues, directly or through the tools you build

What We’re Looking For

We are looking for an experienced software engineer with the judgment and technical depth to build systems that other engineers can trust.

This is not an entry-level AI role. You need a strong understanding of software architecture, maintainability, infrastructure, and production operations. Prior LLM experience is useful but not essential; the ability to evaluate the technology critically and apply it with engineering discipline matters more.

You should be comfortable navigating unfamiliar codebases, designing complex systems, working across application code and infrastructure, and turning ambiguous problems into dependable solutions.

Relevant backgrounds include backend, platform, infrastructure, and developer experience engineering. Experience with internal platforms, developer tooling, distributed systems, or production AI systems is a plus.

Our Stack

Python, Docker, AWS, GitHub Actions, CI/CD and observability tooling, LLM APIs, MCP, and agent orchestration systems.

Strong engineering fundamentals and the ability to learn quickly matter more than knowledge of every technology.

Why Join?

You will help define how software is built across Streem while contributing to the transition to renewable energy.

Your work will be used directly by experienced Product Builders and will have visible consequences across the engineering organization. This is an opportunity to solve difficult, largely unsolved problems with substantial ownership—and to make AI a dependable part of how Streem builds production software.

Additional Information

Recruitment process:

Initial Call with the Head of Engineering
Technical Test with the Head of Engineering
2 calls with other members of the team (among PM/CTO/Dev/CEO)
Final Team meeting to see the fit