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AI Engineer
Posted Today by Next Ventures
Negotiable
Undetermined
Remote
, France
Summary: The AI Engineer role focuses on leveraging AI and large language models to address engineering and operational challenges. The successful candidate will prototype AI-driven solutions, build reference implementations, and promote adoption across teams. This position requires collaboration across various technology stacks and emphasizes a tailored approach to meet team needs. The role is remote and open to candidates across Europe.
Key Responsibilities:
- Identify, scope, and prototype AI-driven solutions for engineering and operational workflows — code generation, automated documentation, incident triage, log analysis, capacity forecasting, and intelligent runbooks.
- Design and build retrieval-augmented generation (RAG) pipelines, agentic workflows, and LLM integrations against internal knowledge bases, codebases, and observability data.
- Develop reusable libraries, SDKs, prompts, and templates that allow other teams to safely adopt AI capabilities with minimal friction.
- Evaluate, benchmark, and select foundation models, vector stores, orchestration frameworks, and supporting infrastructure based on cost, latency, accuracy, and security.
Key Skills:
- Experience with AI and large language models (LLMs).
- Proficiency in software development and engineering practices.
- Knowledge of data retrieval and processing techniques.
- Ability to design and implement AI-driven solutions.
- Strong collaboration and communication skills.
Salary (Rate): undetermined
City: undetermined
Country: France
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
The successful candidate will identify high-value opportunities to apply AI and large language models (LLMs) to real engineering and operational problems, build the reference implementations and tooling that prove those opportunities out, and then drive adoption across teams through enablement, governance, and measurable outcomes. You will work fluently across a broad spectrum of the infrastructure and platform technology stack, meeting teams where they are rather than imposing a single approach.
Key Responsibilities
AI Solution Design & Engineering
- Identify, scope, and prototype AI-driven solutions for engineering and operational workflows — code generation, automated documentation, incident triage, log analysis, capacity forecasting, and intelligent runbooks.
- Design and build retrieval-augmented generation (RAG) pipelines, agentic workflows, and LLM integrations against internal knowledge bases, codebases, and observability data.
- Develop reusable libraries, SDKs, prompts, and templates that allow other teams to safely adopt AI capabilities with minimal friction.
- Evaluate, benchmark, and select foundation models, vector stores, orchestration frameworks, and supporting infrastructure based on cost, latency, accuracy, and security.