Top Artificial Intelligence Jobs in Krakow

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.

Leads reliability, quality, testing, observability, and production-readiness practices for enterprise AI solutions. Establishes automated testing and AI validation frameworks, monitors system health and model quality, improves operational resilience, and oversees incident management, risk assessments, root cause analysis, and executive reporting. Partners with engineering, platform, data, security, product, and business teams to deliver dependable, measurable, production-ready AI systems.

Supports production AI applications, agents, dashboards, and analytics solutions by monitoring reliability, troubleshooting incidents, performing root cause analysis, implementing fixes, and improving service quality. Collaborates with engineering, product, platform, data, and business teams on support priorities and releases. Also contributes to developing, testing, and deploying AI enhancements. The role requires Python, React, API development, production Generative AI and LLM experience, and knowledge of Azure and AWS cloud services.

Lead AI engineering excellence across Danaher by advancing AI-assisted development, engineering standards, CI/CD, DevSecOps, automation, quality frameworks, and developer productivity. Build reusable accelerators, frameworks, templates, and reference implementations while evaluating modern engineering tools and methodologies. Partner with platform, data engineering, product, architecture, and AI teams to improve the design, delivery, deployment, operation, and support of enterprise AI solutions.

Explore, evaluate, and operationalize emerging AI methodologies, models, architectures, and technologies. Design experiments, benchmarks, evaluations, and proofs of concept; develop and productize generative, agentic, multimodal, and machine learning solutions; translate research into reusable enterprise capabilities; and collaborate with platform, data, product, architecture, and engineering teams to scale AI across Danaher.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Develop and maintain Android mobile applications for a fintech product. Design innovative features, improve user experience, and help evolve the mobile platform. Lead Android best practices, identify tooling gaps, reduce technical debt, and optimize CI/CD pipelines. Collaborate in an Agile environment, with potential responsibility for testing practices, continuous integration, and mentoring through technical expertise.

Develop and maintain Android mobile applications for a fintech product used by developers worldwide. The role involves creating innovative mobile features, improving user experience, following Agile practices, and applying Android development best practices. Candidates should have built and published at least one Android app on Google Play. Experience with testing frameworks, scripting languages, and Jenkins is preferred.

Develop and maintain Backbase mobile banking applications for iOS using Swift, UIKit, and SwiftUI. Build reusable components and APIs, leverage AI-assisted development workflows, and deliver production-ready features with strong accessibility, security, performance, and backward-compatibility standards. Collaborate within an Agile Scrum team while writing tests and supporting continuous integration.

Develop and maintain production iOS applications and reusable framework APIs for Backbase Digital Banking. Build Swift components using UIKit, SwiftUI, and the Backbase Design System while ensuring accessibility, security, performance, backward compatibility, and testability. Collaborate within an Agile Scrum team, deliver features end to end, and improve tooling, technical debt, and CI/CD pipelines using AI-assisted development workflows.

Build user-focused web applications and digital banking solutions using Angular, TypeScript, backend integrations, APIs, and microservices. Leverage AI coding assistants and agentic workflows to accelerate development, testing, refactoring, and integrations. Own production-ready features, maintain accessibility, security, performance, and testability standards, and collaborate within cross-functional Scrum teams.

Design and ship agentic voice AI systems for banking, including conversation orchestration, tool calling, runtime architecture, LLM guardrails, grounding, policy enforcement, evaluation, and real-time latency optimization. Maintain production reliability, reduce configuration friction, collaborate across distributed teams, and establish standards for reviewing AI-generated code.

Build modular, config-driven AI video pipelines for gaming advertisements. Integrate generative image, video, text-to-speech, and talking-head models; orchestrate fal.ai jobs with retries, webhooks, rate limits, resumability, and cost tracking; and use FFmpeg for clip assembly, overlays, subtitles, audio mixing, and multiple aspect ratios. Document workflows so marketing teams can operate them without coding and collaborate with creative specialists.

Design, build, deploy, and optimize production LLM agents, MCP servers, RAG and memory architectures, and multi-agent orchestration systems. Develop AI solutions using Amazon Bedrock or Microsoft Foundry, establish evaluation and monitoring frameworks, implement guardrails, analyze failures, and collaborate on scalable AI products. Requires strong experience with agent frameworks, production deployments, cloud AI services, Docker, and CI/CD.

Participate in Veeva’s Consultant Development Program, configuring cloud software, testing features, solving customer problems, managing deliverables, and advising Life Sciences customers. Associates receive intensive onboarding, work directly with customers within three months, and can advance to Consultant in under two years. The role is remote in Poland but requires residence within 60 minutes of Krakow, Warsaw, or Wroclaw and travel up to 20–30% of the time.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Build and maintain PHP and Laravel backend services and APIs for a major product release. Own features from design through deployment and monitoring, integrate agentic AI workflows and LLM-based tooling, optimize performance and reliability, improve security, and mentor engineers. Collaborate independently with a cross-functional team on ambiguous technical challenges while delivering production-ready software.

Build and own production agentic AI runtime components, including context construction, retrieval and tool orchestration, ranking, scoring, guardrails, multilingual quality, latency and cost optimization, and evaluation systems. Diagnose production failures through traces and improve agent reliability for customer-facing commerce applications.

Lead backend development using PHP and Laravel, owning features from design through deployment and monitoring. Build robust APIs, optimize databases and system performance, and improve reliability and security. Integrate agentic AI workflows, including LLM agents, tool-calling pipelines, retrieval, and autonomous task runners. Mentor engineers, collaborate across teams, and deliver production-ready solutions while working in the Toronto time zone.

Design, prototype, deploy, and optimize AI-powered features for construction management applications. Apply LLMs, prompt engineering, model selection, fine-tuning, evaluation, embeddings, vector databases, and RAG. Collaborate with product engineers and SREs to build reliable, scalable, observable, secure production systems. Translate user needs into pragmatic AI solutions while contributing production-grade software and staying current with generative AI developments.

Own and advance the evaluations platform for InPost’s production conversational AI shopping assistant. Responsibilities include LLM-judge pipelines, evaluation datasets, Polish-language golden sets, root-cause analysis, abuse and anomaly detection, reproducible release gates, and eval-driven development. The role provides technical leadership, establishes platform direction, mentors engineers, collaborates with product and business stakeholders, and translates quality goals into measurable definitions.

Support banking AI transformation by managing parallel use-case analysis workstreams, facilitating stakeholder workshops, gathering evidence, documenting processes and requirements, and scoring opportunities. Produce decision-ready dossiers covering business value, feasibility, risk, controls, regulatory obligations, and implementation complexity. Assess responsible AI requirements including the EU AI Act, privacy, cybersecurity, explainability, auditability, human oversight, and reproducibility while maintaining evidence quality and human review.