{"id":186063,"url":"https://alion.io/job/mindbox-engineering-tech-lead","title":"Engineering Tech Lead","company":{"id":53456,"name":"Mindbox","domain":"mindboxgroup.com","url":"https://alion.io/company/mindbox","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Traffit","truth_index":{"grade":"A","score":87,"open_postings":71,"ghost_share":0,"stale_share":0.493,"repost_share":0.028,"time_to_fill_p50_days":53,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":67000,"max_usd":128000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab","optional":false},{"name":"GitLab CI","optional":false},{"name":"Helm","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"LangChain","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Spring Boot","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Terraform","optional":false},{"name":"Tokenization","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-08-19T10:21:06Z","employer_posted_date":"2026-08-19","last_verified_at":"2026-10-18T10:57:48Z","board_verified":true,"closed_at":null,"days_open":60,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":60},"description":"At Mindboxwe connect top IT talents with technology projects for leading enterprises across Europe.\nWe 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.\nAs the Tech Lead, you will collaborate with product teams, domain experts, and AI engineers to enable responsible, scalable, and high-performance AI-driven applications.\nSounds like your kind of challenge?\nResponsibilities\nFlexible cooperation model\nHybrid work setup - 1 day from the office per week\nCollaborative team culture - work alongside experienced professionals eager to share knowledge \nContinuous development - access to training platforms and growth opportunities \nComprehensive benefits - including Interpolska Health Care, Multisport card, Warta Insurance, and more \nHigh quality equipment - laptop and essential software provided \nRequirements\nDesign, build, and deliver production-quality services, ensuring compliance with enterprise controls and security standards.\nEnhance and optimise DecOps pipelines, improving CI/CD automation, testing frameworks, and system observability.\nArchitect and maintain robust systems for high traffic and fault tolerance, optimising global resource allocation.\nDesign and iterate on prompts for a broad set of LLM tasks: instruction-following, structured outputs, summarisation, reasoning, classification, and code generation.\nManage prompt libraries with version control strategies, treating prompts as first-class engineering artefacts.\nImplement evaluation pipelines for prompt performance using tools such as PromptFlow, LangSmith, or custom frameworks.\nArchitect and implement autonomous agent systems, multi-agent workflows, tool calling orchestration, and planning loops with memory-augmented reasoning.\nIntegrate LLM observability capabilities-logging, tracing, evaluation, and automated guardrails-to ensure quality in production environments.\nAdvise on Responsible AI deployment practices, including output validation, human-in-the-loop strategies, and risk mitigation for agentic workflows.\nBuild and optimise Kubernetes deployments (Helm, Kustomize), implement HPA, RBAC and service ingress for secure and scalable operations.\nMaintain and improve CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) for efficient and reliable delivery.\nApply Infrastructure as Code (IaC) methodologies with Terraform, deploying across AWS or GCP environments.\nNote:Detailed project information will be shared during the recruitment process.\nBenefits\nStrong proficiency in Java (Spring Boot): REST APIs, asynchronous/event-driven services, security, and performance tuning.\nAdvanced front-end development experience with React, API integration, and modern UI patterns.\nDatabase expertise: PostgreSQL and in-memory databases (Redis).\nExperience with streaming/messaging platforms, preferably Kafka.\nProven hands-on experience with production LLM applications, beyond prototypes or PoCs.\nDeep understanding of tokenization, context windows, temperature adjustments, and model limitations across major LLM providers.\nStrong capability in designing structured prompts for function/tool calling, generating structured JSON, and handling multi-turn conversations.\nKubernetes (deployments, services, RBAC, Helm/Kustomize), autoscaling and observability principles.\nCI/CD (GitHub Actions, GitLab, Jenkins), IaC with Terraform.\nCloud Infrastructure: AWS or GCP experience essential.\nFamiliarity with LangChain, OpenAI/Azure OpenAI, Anthropic, or comparable LLM ecosystems.\nUnderstanding of model benchmark testing and risk classification in AI workflows.\nKnowledge of secure API/LLM gateway design.\nJoining this project you’llbecome part of Mindbox - a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. 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