Top Artificial Intelligence Jobs in Krakow

Evaluate AI-generated customer service and technical responses for clarity, usefulness, natural language, technical accuracy, JSON validity, formatting, and guideline adherence. Provide clear feedback explaining evaluation decisions. The role requires multilingual fluency, coding knowledge, strong written communication, attention to detail, and consistent judgment. Experience with AI evaluation, quality assurance, APIs, structured data, customer service, software development, or technical writing is preferred.

Own end-to-end product design for MEDvidi’s AI-powered clinical tools, including provider workflows, patient portals, and operational systems. Design human-AI interactions for reviewing, accepting, editing, and rejecting model outputs. Gather requirements independently, validate designs with users, collaborate with engineering through release, and contribute reusable Storybook components, tokens, and documentation. Build functional prototypes in the codebase using Claude Code, Cursor, or similar AI tools.

Develops in-vehicle data quality checks, validation-drive automation, data insights, ETL solutions, APIs, data pipelines, and processing tools for autonomous driving systems. Collaborates with engineering, product, data science, and domain teams while adapting big-data technologies for cloud platforms. Requires Python, C++ or Rust, SQL, scripting, machine learning, data preparation, statistics, and debugging expertise. Experience with cloud, containers, embedded AI, automotive datasets, Git, CI/CD, and ISO 26262 is beneficial.

Builds data engineering solutions for in-vehicle data quality, validation-drive automation, data triaging, and insights supporting hands-off urban driving. Responsibilities include developing APIs, cleaning and organizing raw and processed data, implementing analytics and machine learning solutions, and collaborating with engineering, product, and domain teams. The role involves cloud-based ETL and big-data systems connected to embedded driver-assistance technologies.

Lead Chainguard’s European government affairs and public policy strategy across the UK and Europe. Engage regulators, governments, standards bodies, and industry coalitions; develop policy positions and consultation responses; translate cybersecurity regulations into product, positioning, and customer implications; and establish a scalable policy function. The role requires senior stakeholder engagement, technical policy communication, frequent regional travel, and eventual team-building responsibility.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Writes high-quality long-form content on AI, enterprise technology, infrastructure, and related topics. Responsibilities include researching complex subjects, developing original narratives, producing articles, whitepapers, reports, case studies, website content, and thought leadership, and adapting content for technical and executive audiences. The writer collaborates with subject-matter experts, marketing, and SEO teams while editing for accuracy, clarity, originality, and readability.

Build an AI transformation platform for enterprise process automation and decision support. Responsibilities include integrating CRM, analytics, and BI data; designing schemas and ETL pipelines; building AI agents and MCP servers; developing backend APIs and user-facing tools; and maintaining containerized infrastructure, databases, monitoring, and observability. The role also contributes to agent-platform architecture, documentation, data quality, and client collaboration.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failures, and contribute to architecture and client handovers. The role offers increasing ownership of technical components and decisions while working in distributed, customer-facing delivery teams.

Identify AI opportunities across business teams, scope and prototype solutions, build supporting data pipelines and models, and deploy production AI agents, RAG assistants, and automations. Integrate solutions with Slack, CRM, ticketing, n8n, and MCP; monitor performance through evaluations; and lead AI workshops, office hours, and enablement initiatives. The role requires hands-on ownership from ideation through adoption and impact measurement.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.

Lead Trade Nation’s data and AI strategy, with emphasis on deploying AI into business workflows and enabling measurable adoption. Own the data warehouse’s business-facing gold layer, semantic models, data quality, analytics engineering standards, and self-service analytics. Lead and develop data analysts while partnering with engineering, compliance, and senior stakeholders. The role requires financial services experience, strong SQL and data modelling skills, cloud data platform expertise, and the ability to deliver AI initiatives from concept through production.

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Lead Android platform engineering across R&D by modernizing CI/CD pipelines, establishing multi-module architecture and SDK standards, improving accessibility, security, and performance, and integrating AI-assisted development and testing tools. Partner with pilot teams and stakeholders to drive adoption of new software development practices and guide technical direction across more than 600 engineers.

Develop and maintain Python-based Splunk services and add-ons for large-scale, real-time data ingestion and processing. Participate in requirements, design, development, testing, automation, deployment, code reviews, troubleshooting, and on-call support. Build cloud-based backend solutions using AWS, Azure, or GCP, with LLMs, Generative AI, agentic architecture, and RAG. Improve system reliability, diagnose production issues, and create maintainable, documented software.

Leads the design and delivery of scalable, secure, cloud-native AI applications and reusable full-stack engineering patterns. Defines architecture, integrates AI with instruments, establishes development frameworks, and drives software quality, observability, and DevSecOps practices. Provides technical leadership across global, cross-functional teams and operating companies while mentoring engineers and translating emerging AI technologies into business value.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Conduct full-cycle consultative sales for advanced technical education programs, engaging experienced technology professionals. Qualify goals, explain technical curriculum and career value, handle pricing and financing objections, close high-ticket deals, meet quotas, maintain HubSpot pipeline records, and collaborate with sales leadership and marketing on messaging for an experienced audience.

Build and evolve reusable AI capabilities for construction software products. Design production-grade LLM, retrieval, tool-use, orchestration, and agentic systems; establish evaluation-driven development and reliability standards; and prototype scalable AI solutions. Collaborate with product, engineering, and business stakeholders, guide other engineers, improve AI-assisted development practices, and support systems from experimentation through production rollout and continuous improvement.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Own the end-to-end improvement loop for Elastic’s Context Engine, including agent behavior, evaluations, telemetry, experimentation, safe rollout, and production code. Build and operate AI agents, retrieval tools, memory, APIs, stateful workflows, and data pipelines. Partner with data scientists, engineers, product, and UX to diagnose failures, measure outcomes, evolve public contracts, mentor engineers, and shape the technical roadmap.

Lead the technical vision, design, development, and deployment of AI-powered mobile and edge solutions across Android, iOS, and Windows. Build production-ready machine learning pipelines, AI services, device integrations, observability capabilities, and scalable mobile applications. Mentor engineers and collaborate with product, UX, architecture, and business teams. The role emphasizes IoT, embedded systems, edge AI, generative AI, computer vision, predictive analytics, and regulated-industry applications.