Top Artificial Intelligence Jobs in Poland

The Financial Controller will oversee financial operations, reporting, forecasting, budgeting, cost management, and financial analysis. Responsibilities include monitoring profitability, managing LLM-related app spend, controlling accounting and payment processes, preparing management reports and models, investigating variances, and advising stakeholders on financial decisions. The role also involves presenting analyses to C-level leaders and improving financial policies and procedures.

Generates realistic images and short- and long-form videos using modern AI generation models. Builds automated workflows and streaming content-generation systems for scalable production, applying prompt design, LLMs, Codex, and Claude Code.

Design, develop, test, deploy, and maintain secure cloud-native enterprise applications using full-stack technologies. Build AI-enabled solutions, reusable engineering assets, CI/CD pipelines, automated quality controls, and production-ready prototypes. Apply specification-driven development, DevSecOps, automated testing, cloud engineering, responsible AI, and InnerSource practices. Collaborate with business, product, architecture, security, platform, and operations teams to transition ideas and proofs of concept into scalable, supported production services.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Build unstructured-data ingestion and context-layer pipelines for an investment group. Responsibilities include historical backfills, document parsing, entity resolution, deduplication, incremental API synchronization, embeddings, vector and graph storage, access scoping, lineage, PII protection, orchestration, monitoring, cost control, and operational runbooks.

Build and extend Relativity’s Python-based agent runtime using LangGraph, LangChain, and Deep Agents. Develop orchestration, tool calling, memory, human-in-the-loop review, streaming, checkpointing, protocols, and multi-agent capabilities. Deliver tested, production-ready cloud-native systems with PostgreSQL, Azure, Docker, and Kubernetes while collaborating with application and applied science teams. Contribute to design reviews and safely move AI capabilities from experimentation into production.

Design and build Relativity’s agent runtime and AI platform foundations using Python and agentic AI frameworks. Develop orchestration, tool calling, state management, memory, protocol support, reusable abstractions, and cloud-native services. Collaborate with engineering teams to establish scalable platform capabilities, evaluate emerging agent architectures, and support reliable LLM system upgrades across products.

Lead a cross-functional squad to define product vision, roadmap and deliver new features for institutional English assessments. Translate business needs into requirements, write and prioritize epics and user stories, run agile ceremonies, collaborate with UX/development/marketing/operations, use data to iterate, and mentor colleagues to achieve measurable business outcomes.

Design and deliver scalable, secure solutions for R&D labs by defining reference architectures, data models, taxonomies and NFRs. Lead solution lifecycle from concept and PoCs through implementation, manage technical debt, perform vendor assessments, and align stakeholders and architecture governance to drive adoption and business value.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Leads a new Warsaw-based engineering team building AI-powered technology for Netflix Consumer Products. Responsibilities include hiring, coaching, setting technical direction, managing execution, shaping roadmaps with product and cross-functional partners, advising on technical decisions, improving stability and performance, reducing technical debt, and collaborating with engineers and stakeholders across Poland and the United States.

Build and iterate AI systems spanning computer vision, image manipulation, video generation, and agentic data analysis. Own the full pipeline from model research and API integration through scalable web application deployment. Develop rapid MVPs using AI-assisted tools, orchestrate multiple models into autonomous workflows, and test solutions in e-commerce operations before scaling them into SaaS products.

Drives value realization for software, automation, digital engineering, and AI investments. Develops ROI and business case analyses, defines KPIs and success criteria, tracks benefits against plans, evaluates technology use cases, and prepares executive dashboards and investment recommendations. Partners with engineering, finance, product, architecture, PMO, and transformation teams to prioritize investments, validate post-implementation benefits, and improve governance practices.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Design, implement, and optimize end-to-end AI pipelines including model training, deployment, monitoring, and inference. Build IaC and CI/CD workflows, ensure secure compliant production deployments, design deep learning models for NLP/vision/speech, troubleshoot performance, and mentor junior AI/Ops engineers while collaborating with stakeholders.

Own end-to-end features across Go backend services and React/TypeScript frontend applications. Design, develop, and debug high-load distributed systems, APIs, integrations, and event-driven services. Use AI coding agents as part of daily development, critically reviewing and verifying generated output. Contribute to architecture decisions, resolve complex production issues, and improve engineering practices for AI-assisted delivery.

Deliver AI fluency training, coach engineering teams on AI-assisted development, pair with developers, maintain internal AI agents and workflows, create enablement content, assess adoption maturity, and track productivity improvements. Collaborate with Architecture and Platform teams to support AI-first engineering practices and broader developer experience initiatives across the software delivery lifecycle.

Owns the development, validation, and continuous improvement of AI-powered analytics solutions, including Talk2Data and agent-ready data. Defines analytical requirements, evaluation metrics, quality frameworks, and data models; validates large datasets and AI outputs; collaborates with data engineers and business stakeholders; supports governance, deployment, enablement, and proof-of-concept initiatives; and evaluates AI tools and integrations.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Lead finance for a fast-growing AI-native B2B SaaS company, partnering with C-level leaders on strategic decisions. Manage a three-person controlling and accounting team; own budgeting, forecasting, SaaS KPI reporting, cash flow, FX hedging, accounting structures, intangible asset capitalization, and cost optimization. Provide financial modeling, profitability analysis, business recommendations, and tax collaboration while maintaining strong accounting and reporting standards.

Translate legal expertise into AI-powered workflows by designing, configuring, and testing Libra Assistants. Partner with clients to map processes, run pilots, enable adoption, and provide product feedback to improve prompt quality and accuracy. Create learning materials and drive high customer satisfaction while working cross-functionally with Product, Engineering, Sales, and Customer Success.

Leads the design and delivery of secure, scalable, LLM-enabled applications spanning APIs, user interfaces, orchestration pipelines, vector databases, and enterprise integrations. Builds reusable AI tooling, SDKs, and governance processes; deploys solutions across cloud environments; ensures observability, operational excellence, and responsible AI compliance. Partners with business stakeholders, architects, security teams, and strategic vendors to prioritize high-value use cases, guide platform strategy, and deliver production-ready systems.

Build and enhance RAG systems, AI components, backend services, data pipelines, REST APIs, evaluation harnesses, and production AWS deployments. Write tests, investigate model failure modes, support containerized CI/CD releases, document solutions, and contribute to architecture and client handoffs. The role offers senior guidance while progressively increasing ownership of technical decisions and system components.