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

~21.7k - 26.1k PLN21 700 - 26 100 PLN/ mies./ mies.B2BB2B (netto)

Brak informacji o wynagrodzeniu

SeniorHybryda·KrakówFull-time·B2B·Umowa o pracę

#402709·Dodano dwa miesiące temu·1

Źródło: ITDS

Tech Stack / Keywords

Our client is a pioneering technology company shaping the future of intelligent systems, focusing on AI and cloud-native solutions.

At least 7 years of software engineering experience focused on AI or cloud-native solutions.
Strong proficiency in Java and Spring Boot, including REST APIs, event-driven services, security, and performance tuning.
Solid React development skills and experience with API integration.
Experience with relational and in-memory databases such as PostgreSQL and Redis.
Experience with messaging and streaming platforms like Kafka.
Expertise in 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, Braintrust, or custom pipelines.
Understanding of Kubernetes deployments, services, ingress, Helm, Kustomize, HPA, and RBAC.
Experience with CI/CD tools including GitHub Actions, GitLab CI, Jenkins and Infrastructure as Code with Terraform.
Hands-on knowledge of cloud platforms such as AWS, GCP, or Azure.

Nice to have:

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

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

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

ITDS

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