Senior AI & Cloud-Native Engineering Lead – LLM and DevOps Expertise

Description

As a Senior AI & Cloud-Native Engineering Lead, you will lead the design and delivery of production-quality AI services, develop agentic systems, and optimize DevOps pipelines in a cloud-native environment, with a focus on large language models (LLMs) and automation.

Your main responsibilities

• Lead the development, deployment, and maintenance of high-quality production AI services, ensuring alignment with business controls.
• Design, optimize, and iterate prompts for LLM use cases including instruction following, structured output, classification, summarization, and code generation.
• Build and manage prompt libraries with versioning strategies, treating prompts as critical engineering artifacts.
• Collaborate with product and domain teams to translate business needs into precise prompt specifications and AI workflows.
• Architect and implement agentic AI systems, including autonomous agents, multi-agent pipelines, tool-use workflows, planning loops, and memory-augmented reasoning modules.
• Enhance observability of LLM operations through logging, tracing, evaluation pipelines, and safety guardrails, maintaining system reliability.
• Provide expertise on responsible AI deployment, integrating output validation, human-in-the-loop design, and risk mitigation strategies.

You’re ideal for this role if you have

• At least 7 years of experience in software engineering, with a focus on AI or cloud-native solutions.
• Strong proficiency in Java / Spring Boot, including REST APIs, event-driven services, security, and performance tuning.
• Solid React development skills and experience with API integration.
• Hands-on experience with relational and in-memory databases such as PostgreSQL and Redis.
• Experience with messaging and streaming platforms such as Kafka or equivalent.
• Proven expertise engineering prompts for production LLM applications, including tokenization, context limits, temperature tuning, and model-specific parameters.
• Familiarity with prompt evaluation frameworks and tooling, such as PromptFlow, LangSmith, and Braintrust, or custom evaluation pipelines.
• Good understanding of Kubernetes deployments, services, ingress, Helm, Kustomize, HPA, and RBAC.
• Experience with CI/CD pipelines, including GitHub Actions, GitLab CI, or Jenkins, and Infrastructure as Code using Terraform.
• Hands-on knowledge of cloud platforms such as AWS, GCP, or Azure.

It is a strong plus if you have

• Certifications or experience integrating AI in enterprise environments.
• Background in responsible AI practices, output validation, and human-in-the-loop systems.

Language required for the role

• Fluent English, with excellent communication skills.

Eligibility for the role

• Only candidates with an existing legal right to work in the European Union will be considered.

Apply with a CV, preferably in English, along with a statement confirming consent to the processing and storage of personal data.