Engineering Tech Lead

Nasze wymagania:
Strong proficiency in Java (Spring Boot): REST APIs, asynchronous/event-driven services, security, and performance tuning.
Advanced front-end development experience with React, API integration, and modern UI patterns.
Database expertise: PostgreSQL and in-memory databases (Redis).
Experience with streaming/messaging platforms, preferably Kafka.
Proven hands-on experience with production LLM applications, beyond prototypes or PoCs.
Deep understanding of tokenization, context windows, temperature adjustments, and model limitations across major LLM providers.
Strong capability in designing structured prompts for function/tool calling, generating structured JSON, and handling multi-turn conversations.
Kubernetes (deployments, services, RBAC, Helm/Kustomize), autoscaling and observability principles.
CI/CD (GitHub Actions, GitLab, Jenkins), IaC with Terraform.
Cloud Infrastructure: AWS or GCP experience essential.
Familiarity with LangChain, OpenAI/Azure OpenAI, Anthropic, or comparable LLM ecosystems.
Understanding of model benchmark testing and risk classification in AI workflows.
Knowledge of secure API/LLM gateway design.

O projekcie:
We are looking for an experienced Engineering Tech Lead to drive the design, delivery, and optimization of production-grade AI-enabled systems, DecOps pipelines, and agentic AI workflows. This is a highly technical and strategic leadership role that combines advanced full-stack engineering with deep expertise in LLM integration, prompt engineering, and DevOps.
As the Tech Lead, you will collaborate with product teams, domain experts, and AI engineers to enable responsible, scalable, and high-performance AI-driven applications.
Sounds like your kind of challenge?

Zakres obowiązków:
Design, build, and deliver production-quality services, ensuring compliance with enterprise controls and security standards.
Enhance and optimise DecOps pipelines, improving CI/CD automation, testing frameworks, and system observability.
Architect and maintain robust systems for high traffic and fault tolerance, optimising global resource allocation.
Design and iterate on prompts for a broad set of LLM tasks: instruction-following, structured outputs, summarisation, reasoning, classification, and code generation.
Manage prompt libraries with version control strategies, treating prompts as first-class engineering artefacts.
Implement evaluation pipelines for prompt performance using tools such as PromptFlow, LangSmith, or custom frameworks.
Architect and implement autonomous agent systems, multi-agent workflows, tool calling orchestration, and planning loops with memory-augmented reasoning.
Integrate LLM observability capabilities—logging, tracing, evaluation, and automated guardrails—to ensure quality in production environments.
Advise on Responsible AI deployment practices, including output validation, human-in-the-loop strategies, and risk mitigation for agentic workflows.
Build and optimise Kubernetes deployments (Helm, Kustomize), implement HPA, RBAC and service ingress for secure and scalable operations.
Maintain and improve CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) for efficient and reliable delivery.
Apply Infrastructure as Code (IaC) methodologies with Terraform, deploying across AWS or GCP environments.
Note: Detailed project information will be shared during the recruitment process.

Oferujemy:
Flexible cooperation model – choose the form that suits you best (B2B, employment contract, etc.)
Hybrid work setup – 1 day from the office per week
Collaborative team culture – work alongside experienced professionals eager to share knowledge
Continuous development – access to training platforms and growth opportunities
Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more
High quality equipment – laptop and essential software provided