AI/ML Engineer

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI solutions, including agentic workflows and RAG pipelines integrated into enterprise systems. The position emphasizes software engineering excellence, cloud-based AI services, and orchestration of LLM capabilities rather than model research. You will build reliable, secure, and observable AI services integrated with internal platforms and APIs. 🗂️ Requirements: 5+ years of professional software development experience, Strong background in designing and operating production systems, Proficiency in Python or another backend language for AI systems, Experience building and integrating RESTful APIs, Understanding of distributed systems fundamentals, Experience with API integrations and event-driven architectures, Solid SQL and database design knowledge, Experience with vector search, Hands-on experience building end-to-end LLM applications, Experience implementing RAG pipelines, Strong knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and regression testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Embeddings, VectorSearch, AzureFunctions, AzureStorage, KeyVault, AppConfiguration, ApplicationInsights 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI systems, including agentic workflows and RAG pipelines integrated into enterprise platforms. The position emphasizes backend engineering, API integrations, and orchestration of LLM capabilities in secure, scalable cloud environments rather than ML research. The role also includes mentoring engineers and establishing best practices for reliable, observable AI services. 🗂️ Requirements: 5+ years professional software development experience, Proficiency in Python, Experience building production LLM applications, Hands-on experience with RAG systems, Experience designing and integrating RESTful APIs, Strong understanding of distributed systems fundamentals, Experience with SQL databases and performance optimization, Experience with vector search, Experience integrating external services via APIs, Knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Microservices, DistributedSystems, Concurrency, AsyncIO, VectorSearch, Embeddings, Caching, AzureFunctions, Storage, KeyVault, AppConfiguration, ApplicationInsights, ServiceBus, EventHubs 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Offer for an AI/ML Engineer to design and deploy end-to-end AI solutions in industrial environments, focusing on Computer Vision 2D/3D, sensor data analysis, and Physical AI. The role involves building production-ready models, implementing MLOps practices, and validating solutions with robots, cameras, and sensors. It targets practical AI deployments with real impact on physical systems. 🗂️ Requirements: Higher education in Computer Science, AI/ML, Mathematics, Physics, Robotics or related field, Minimum 2 years of commercial experience in AI/ML, Experience deploying ML models to production environments, Very good knowledge of Python, Experience with Deep Learning frameworks, Experience in Computer Vision 2D/3D, Experience in time-series analysis, Knowledge of Git and Docker, Experience with MLOps tools, Ability to use AI coding assistants, English level B2 or higher 📃 Skills: Python, NumPy, pandas, scikit-learn, PyTorch, TensorFlow, ComputerVision, TimeSeries, Git, Docker, MLflow, DVC, W&B, ONNX, Jetson, ROS, ROS2 🏢 Description: Poszukujemy AI/ML Engineera do rozwijania nowoczesnych rozwiązań z obszaru Computer Vision, analizy danych z czujników oraz Physical AI. Zakres obowiązków: Projektowanie i rozwój end-to-end pipeline'ów AI/ML. Budowa i rozwój modeli Computer Vision 2D/3D (skany 3D, point clouds). Tworzenie modeli time-series do analizy sygnałów z czujników (siła, akcelerometr). Wdrażanie rozwiązań anomaly detection oraz rozpoznawania geometrii detali. MLOps: wersjonowanie, CI/CD, monitoring modeli produkcyjnych. Testowanie rozwiązań na stanowiskach z robotami, kamerami i czujnikami. Współpraca z zespołem technicznym oraz dokumentacja projektowa. Wymagania: Wykształcenie wyższe (informatyka, AI/ML, matematyka, fizyka, automatyka i robotyka lub pokrewne). Minimum 2 lata doświadczenia komercyjnego w AI/ML. Doświadczenie we wdrażaniu modeli do środowiska produkcyjnego. Bardzo dobra znajomość Python (NumPy, pandas, scikit-learn). Deep Learning (PyTorch lub TensorFlow). Computer Vision 2D/3D oraz analiza szeregów czasowych. Znajomość Git, Docker oraz narzędzi MLOps (MLflow, DVC, W&B). Umiejętność pracy z narzędziami AI wspierającymi programowanie (Cursor, Codex, Claude Code). Samodzielność, inicjatywa i nastawienie na praktyczne wdrożenia. Język angielski na poziomie min. B2. Mile widziane: Doświadczenie z point clouds, anomaly detection i DoE. Edge deployment (ONNX, Jetson), ROS/ROS2. Praca z czujnikami force-torque. Doświadczenie w projektach startupowych lub B+R. Znajomość Foundation Models for Robotics (VLA). Publikacje naukowe lub doktorat. Jeśli chcesz rozwijać rozwiązania AI działające w rzeczywistym środowisku przemysłowym i mieć realny wpływ na produkt – zapraszamy do aplikowania.

🏢 Summary: The role involves designing, developing, and deploying AI and LLM-based solutions in a cloud environment, with a focus on building and enhancing Data, Analytics, MLOps, and LLMOps platforms. The position covers full lifecycle management of machine learning and language models, including deployment, monitoring, and optimization. The engineer will contribute to data architecture and distributed systems supporting AI-driven products. 🗂️ Requirements: Experience as LLM Engineer or similar AI/Data role, Around 3 years of experience with Python, Experience building Data, Analytics, MLOps or LLMOps platforms in cloud environments, Experience with Azure cloud, Knowledge of full ML model lifecycle management in cloud, Experience with Big Data open-source tools: Kafka, Airflow, Presto, Spark, Experience in database design and data modeling, Experience working with distributed systems 📃 Skills: Python, Azure, LLM, AI, MLOps, LLMOps, Kafka, Airflow, Presto, Spark, SQL, BigData 🏢 Description: Dla naszego klienta, innowacyjnej firmy z branży ubezpieczeniowej, poszukujemy : AI / LLM Engineera Zakres obowiązków: Projektowanie, rozwój i wdrażanie rozwiązań opartych o LLM oraz technologie AI w środowisku chmurowym, Tworzenie i rozwój komponentów wspierających budowę nowoczesnych platform Data / Analytics / MLOps / LLMOps, Zarządzanie cyklem życia modeli machine learningowych i rozwiązań opartych o modele językowe, w tym ich wdrażaniem, monitorowaniem i optymalizacją, Współpraca przy budowie i doskonaleniu procesów automatyzujących rozwój, testowanie i utrzymanie rozwiązań AI, Współpraca z zespołami Data, Analytics oraz IT w celu zapewnienia spójności architektury i wysokiej jakości dostarczanych rozwiązań, Udział w projektowaniu architektury danych i rozwiązań rozproszonych wspierających rozwój produktów opartych o AI. Wymagania Doświadczenie na stanowisku LLM Engineer lub w zbliżonej roli z obszaru danych i AI, Około 3 lata doświadczenia z Pythonem, Doświadczenie w tworzeniu i rozwijaniu platform z obszaru Data, Analytics, MLOps lub LLMOps w środowisku chmurowym, preferencyjnie Azure, Znajomość zagadnień związanych z pełnym cyklem życia modeli machine learningowych, w tym ich wdrażaniem, utrzymaniem oraz monitoringiem w środowisku chmurowym, Doświadczenie w pracy z narzędziami open source wykorzystywanymi w ekosystemie Big Data, takimi jak Kafka, Airflow, Presto, Spark, Doświadczenie w projektowaniu baz danych, modelowaniu danych oraz pracy z systemami rozproszonymi, Samodzielność, inicjatywa oraz umiejętność efektywnej pracy w zespole. Pracodawca oferuje: Zatrudnienie w oparciu o umowę o pracę lub B2B, Atrakcyjne wynagrodzenie, Pracę w trybie hybrydowym lub zdalnym, Elastyczne godziny rozpoczęcia pracy, Pracę w zespole rozwijającym innowacje cyfrowe w obszarze ubezpieczeń, Realną autonomię i wpływ na kierunek rozwoju platformy oraz rozwiązań biznesowych, Dostęp do nowoczesnych narzędzi i rozwiązań cloud-native, Obszerny pakiet benefitów pozapłacowych: prywatna opieka medyczna, karta sportowa, dofinansowanie do szkoleń/studiów/kursów językowych, Zniżki na produkty własne.

🏢 Summary: AI Engineer role focused on designing and implementing GenAI solutions, particularly RAG-based systems using LLM services. The position involves prototyping AI assistants, developing and deploying production-grade solutions, and working with Azure-based AI services. The role combines hands-on engineering with analytical prototyping in commercial AI projects. 🗂️ Requirements: Higher education in Computer Science, Data Science, Mathematics, Econometrics or related field, Minimum 3 years of experience as AI Engineer delivering LLM-based projects, Very good knowledge of Azure environment, Very good knowledge of Python, Strong knowledge of RAG techniques and prompt engineering, Experience implementing and integrating LLMs in Python, Basic knowledge of NLP, Knowledge of code review practices and CI/CD pipelines using Gitlab 📃 Skills: Python, Langchain, Streamlit, MLFlow, Azure, OpenAI, DocumentIntelligence, AISearch, AppService, Functions, DevOps, Databricks, Sharepoint, RAG, LLM, NLP, Gitlab, CICD 🏢 Description: Firma Algomine, należąca do grupy TTPSC, poszukuje AI Engineer Zakres obowiązków: Projektowanie i implementacja rozwiązań z obszaru GenAI W szczególności budowa rozwiązań typu RAG (m.in. z użyciem Langchain) z wykorzystaniem gotowych modeli/usług LLM Prototypowanie aplikacji typu asystent AI dla użytkowników biznesowych (m.in. w oparciu o Streamlit) Development i deployment rozwiązań o charakterze produkcyjnym Bliska współpraca z klientem, analiza procesów, zbieranie wymagań Praca na projektach analitycznych i konsultingowych Prototypowanie rozwiązań analitycznych (testowanie podejść) Prezentacja koncepcji i business case, omawianie uzyskiwanych wyników Ewaluacja nowych technologii, bibliotek, podejść oraz proponowanie innowacyjnych rozwiązań Stos Technologiczny Open source: Python, Langchain, Streamlit, MLFlow Azure: OpenAI, Document Intelligence, AI Search, App Service, Functions, DevOps, Databricks Sharepoint Poszukiwane kompetencje: Wykształcenie wyższe informatyczne lub pokrewne np.: data science, matematyka, ekonometria, metody ilościowe Ponad 3-letnie doświadczenie w roli inżyniera AI we wdrażaniu komercyjnych lub naukowych projektów wykorzystujących usługi LLM Bardzi dobra znajomość środowiska Azure Bardzo dobra znajomość języka Python Dobra znajomość technik RAG, prompt engineering, używania LLM oraz ich implementacji w Python Podstawowa znajomość zagadnień przetwarzania języka naturalnego (NLP) Znajomość dobrych praktyk programistycznych (Code review, Gitlab, CI/CD) Dobra komunikacja, umiejętność prowadzenie rozmów z odbiorcą biznesowym Dobra znajomość języka angielskiego Mile widziane: Doświadczenie w obszarze doradztwa i consultingu Doświadczenie we wdrażaniu projektów data science/AI od startu do uruchomienia produkcyjnego Znajomość Azure Databricks Znajomość PyTorch, TensorFlow Doświadczenie w operacjonalizacji modeli Certyfikaty potwierdzające posiadane umiejętności Oferujemy: Udział w zróżnicowanych i zaawansowanych technologicznie projektach GenAI Nowoczesny stack technologiczny i otwartość na wdrażanie nowych rozwiązań Pracę w dedykowanym zespole Data Science/AI Prywatna opieka medyczna i karta sportowa Elastyczny czas pracy i możliwość 100% pracy zdalnej Spotkania integracyjne oraz niezapomniane imprezy firmowe

🏢 Summary: Senior-level role focused on designing and delivering scalable AI/ML solutions, including LLMs, RAG, and agent-based systems, from architecture to production deployment. The position involves leading technical decisions, writing high-quality Python code, and building cloud-based microservices solutions. The role also requires translating business needs into robust, production-ready AI systems. 🗂️ Requirements: Several years of software development experience (senior-level), Strong Python proficiency, Solid understanding of ML/AI ecosystem (LLMs, NLP, deep learning), Hands-on experience with RAG, prompt engineering, agent-based systems, Experience with microservices architecture, Experience with databases, Experience with Kubernetes, Experience with CI/CD pipelines, Experience with Azure cloud, English proficiency 📃 Skills: Python, LLMs, RAG, NLP, DeepLearning, PromptEngineering, Microservices, Databases, Kubernetes, CICD, Azure, GCP, Java 🏢 Description: Responsibilities: Design and develop scalable AI/ML solutions (LLMs, RAG, agentic systems) Write high-quality, testable Python code Lead technical architecture and make key design decisions for critical projects Own end-to-end delivery of solutions, from design to production deployment Collaborate with business stakeholders and translate requirements into technical solutions Requirements: Several years of experience as a software developer (senior-level preferred) Very strong Python skills and solid understanding of the ML/AI ecosystem (LLMs, NLP, deep learning) Hands-on experience with RAG, prompt engineering, and agent-based systems Experience with microservices architecture, databases, Kubernetes, and CI/CD pipelines Experience with Azure cloud (GCP as a plus) Basic familiarity with Java is a plus Strong English communication skills

🏢 Summary: The offer is for an MLOps / AI Engineer to design, implement and maintain AI/ML solutions for banking and financial sector projects. The role focuses on building MLOps environments, automating training and deployment processes, and managing cloud-based AI infrastructure in production. You will support the full lifecycle of ML models, including monitoring and optimization in production environments. 🗂️ Requirements: 3–4 years of experience as MLOps Engineer, AI Engineer, Machine Learning Engineer or similar, Strong knowledge of Python, Experience building and maintaining ML solutions in production environments, Experience with Docker and containerization, Experience with AWS, Azure or Google Cloud Platform, Knowledge of CI/CD and deployment automation, Experience working with Git, Knowledge of AI/ML model monitoring in production 📃 Skills: Python, Docker, AWS, Azure, GCP, CICD, Git, MLOps, MachineLearning, Monitoring, Cloud 🏢 Description: O projekcie Poszukujemy MLOps / AI Engineera do realizacji innowacyjnych projektów dla sektora bankowego i finansowego. Osoba na tym stanowisku będzie odpowiedzialna za projektowanie, wdrażanie oraz utrzymanie rozwiązań opartych o sztuczną inteligencję, uczenie maszynowe oraz nowoczesne platformy danych. Będziesz współpracować z zespołami Data Science, Data Engineering i DevOps, wspierając cały cykl życia modeli AI – od budowy środowisk treningowych po wdrożenie modeli na środowiska produkcyjne. Twój zakres obowiązków Projektowanie i rozwój środowisk MLOps wspierających wdrażanie modeli AI/ML Automatyzacja procesów trenowania, testowania oraz wdrażania modeli Budowa i utrzymanie pipeline'ów ML oraz Data Pipelines Monitorowanie jakości, wydajności i stabilności modeli produkcyjnych Współpraca z Data Scientistami oraz zespołami developerskimi Implementacja rozwiązań opartych o Generative AI i Large Language Models (LLM) Zarządzanie infrastrukturą chmurową wspierającą rozwiązania AI Tworzenie dokumentacji technicznej oraz dobrych praktyk w zakresie AI Engineering Optymalizacja kosztów i wydajności środowisk AI/ML Nasze wymagania Minimum 3–4 lata doświadczenia na stanowisku MLOps Engineer, AI Engineer, Machine Learning Engineer lub pokrewnym Bardzo dobra znajomość Python Doświadczenie w budowie i utrzymaniu rozwiązań Machine Learning w środowiskach produkcyjnych Znajomość Docker oraz konteneryzacji aplikacji Doświadczenie z platformami chmurowymi AWS, Azure lub Google Cloud Platform Znajomość CI/CD oraz automatyzacji procesów wdrożeniowych Doświadczenie w pracy z Git Znajomość zagadnień związanych z monitoringiem modeli AI Umiejętność współpracy z zespołami Data Science i Engineering Znajomość języka angielskiego na poziomie B2–C1 Mile widziane Doświadczenie z MLflow Znajomość Apache Airflow Doświadczenie z Kubernetes Praktyczna znajomość PyTorch lub TensorFlow Doświadczenie z Large Language Models (LLM) Znajomość frameworków takich jak LangChain, LangGraph lub LlamaIndex Doświadczenie z bazami wektorowymi (Pinecone, Weaviate, ChromaDB, Qdrant) Znajomość rozwiązań RAG (Retrieval-Augmented Generation) Doświadczenie w projektach Generative AI Znajomość Apache Kafka Doświadczenie w sektorze bankowym lub finansowym Oferujemy Udział w nowoczesnych projektach związanych ze sztuczną inteligencją i uczeniem maszynowym Możliwość pracy zdalnej lub hybrydowej Elastyczne godziny pracy Stabilną współpracę przy długoterminowych projektach Możliwość rozwoju kompetencji w obszarze AI, MLOps i Generative AI Pracę z najnowszymi technologiami chmurowymi i rozwiązaniami AI Współpracę z ekspertami Data Science, AI oraz Cloud Engineering Realny wpływ na rozwój innowacyjnych produktów i usług Atrakcyjne wynagrodzenie adekwatne do doświadczenia i kompetencji Jeżeli chcesz rozwijać rozwiązania oparte na sztucznej inteligencji, wdrażać modele ML na skalę produkcyjną oraz uczestniczyć w projektach wykorzystujących Generative AI i LLM – zapraszamy do aplikowania.

🏢 Summary: Opportunity to join a newly formed AI team in the banking sector to build a modern AI-native platform from scratch. The role focuses on designing and delivering production-grade solutions using LLMs, RAG, and agent-based architectures, while shaping AI strategy and architectural decisions. You will develop secure, transparent, and scalable AI systems that drive real business value in a regulated financial environment. 🗂️ Requirements: At least 3 years of experience in AI/ML, Minimum 5 years of experience in product development, Strong Python skills, Hands-on experience with LLMs, RAG, and agent-based systems in production, Experience with AI frameworks such as Agno, LangChain, LlamaIndex or similar, Knowledge of prompt engineering and AI model evaluation, Experience with Azure or AWS, Understanding of vector databases and embeddings, Experience with workflow orchestration tools (Temporal, Prefect, Airflow), Ability to design scalable and reliable AI solutions, Experience in model monitoring and MLOps practices, Ability to make architectural decisions and assess business value of AI, Fluent English 📃 Skills: Python, LLM, RAG, LangChain, LlamaIndex, Agno, Azure, AWS, Temporal, Prefect, Airflow, MLOps, Embeddings, VectorDB 🏢 Description: We are looking for an experienced Senior AI Engineer to join a newly formed AI team delivering a strategic initiative in the banking sector. This is a unique opportunity to co-create a modern AI-native platform from scratch and influence the direction of AI within the organisation. In this role, you will design and develop solutions based on LLMs, RAG systems, and agent-based architectures to support data integration and transformation processes. You will contribute to key decisions around AI strategy, model selection, architecture, and quality standards. We are seeking a candidate with strong technical skills and hands-on experience in building production-grade AI solutions—someone who understands where AI brings real business value and can deliver high-quality, transparent, and secure solutions in a financial environment. Your tasks Design and develop solutions based on LLMs, RAG, and agent-based architectures Co-create and execute an AI strategy for a modern banking platform Select models, frameworks, and approaches for production-grade AI solutions Build systems for data integration, transformation, and validation automation Define prompt engineering, model evaluation, and AI quality standards Develop monitoring, evaluation, and continuous improvement mechanisms Collaborate with engineering and product teams on new features Ensure high quality, transparency, and auditability of AI outputs Contribute to key architectural decisions and AI direction Mentor and share knowledge within the AI team Requirements At least 3 years in AI/ML and a minimum of 5 years in product development Strong Python skills Hands-on experience with LLMs, RAG, and agent-based systems in production Familiarity with frameworks such as Agno, LangChain, LlamaIndex, or similar Knowledge of prompt engineering and AI model evaluation Experience with Azure or AWS Understanding of vector databases and embeddings Experience with workflow orchestration tools (e.g., Temporal, Prefect, Airflow) Ability to design scalable, reliable AI solutions Experience in model monitoring and MLOps practices Capability to make architectural decisions and assess the business value of AI Strong collaboration skills with technical and business stakeholders Fluent English Nice-to-have requirements Previous work in financial services, fintech, or other regulated industries Knowledge of compliance, auditability, and AI security Familiarity with MLOps and large-scale ML/LLM deployments Experience fine-tuning open-source models for specific domains Proven track record in developing AI solutions for data platforms, analytics, or SaaS products Background in AI R&D projects Publications, conference speaking, or open-source contributions Experience building and scaling technical teams What we offer Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022 Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more Comfortable workplace – class A offices or remote work Dozens of fascinating projects for prestigious brands from all over the world PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers Investment in your growth – meetups, webinars, training platform and technology blog – you choose Fantastic atmosphere created by all Sii Power People If you want to work on systems with high operational significance — apply now!

🏢 Summary: The role involves developing and maintaining backend components in Python while supporting the implementation of AI-driven features within products. The position focuses on integrating AI/ML components, working with data, and contributing to simple model development and backend services. It is suited for candidates with commercial Python experience and initial hands-on exposure to AI/ML technologies. 🗂️ Requirements: Minimum 2 years of commercial experience with Python, Hands-on experience with AI/ML features, Experience working with APIs, Experience developing backend services, Understanding of software development best practices 📃 Skills: Python, AI, ML, APIs, TensorFlow, PyTorch, scikit-learn, OpenAI, LLM, NLP, AWS, GCP, Azure 🏢 Description: We are looking for a Junior/Regular AI Engineer to join our team and support the development of AI-powered features within our products. This role is ideal for someone with solid Python skills and initial hands-on experience working with AI/ML components. Responsibilities Develop and maintain backend components using Python Support the implementation of AI-driven features and capabilities within products Collaborate with product and engineering teams to integrate AI solutions Work with data and assist in building simple ML/AI models or integrations Contribute to code quality, testing, and documentation Requirements Minimum 2 years of commercial experience with Python Initial hands-on experience with AI/ML features (e.g. working with models, APIs like OpenAI, basic ML pipelines, etc.) Understanding of software development best practices Experience working with APIs and backend services Good problem-solving skills and willingness to learn in the AI space Nice to have Experience with libraries/frameworks such as: TensorFlow, PyTorch, scikit-learn Familiarity with LLMs, NLP, or Generative AI Experience with cloud platforms (AWS, GCP, Azure) Basic knowledge of data engineering concepts We offer Opportunity to work on real AI-driven products Exposure to modern AI technologies and tools Supportive team and learning environment

🏢 Summary: The role involves developing and maintaining Python-based backend components while supporting the implementation of AI-driven features in products. The position focuses on integrating AI/ML solutions, working with data, and contributing to simple model development and backend services. It is suited for candidates with commercial Python experience and initial hands-on exposure to AI technologies. 🗂️ Requirements: Minimum 2 years commercial experience with Python, Hands-on experience with AI/ML features, Experience working with APIs, Experience developing backend services, Understanding of software development best practices 📃 Skills: Python, AI, ML, APIs, TensorFlow, PyTorch, scikit-learn, OpenAI, LLM, NLP, AWS, GCP, Azure 🏢 Description: We are looking for a Junior/Regular AI Engineer to join our team and support the development of AI-powered features within our products. This role is ideal for someone with solid Python skills and initial hands-on experience working with AI/ML components. Responsibilities Develop and maintain backend components using Python Support the implementation of AI-driven features and capabilities within products Collaborate with product and engineering teams to integrate AI solutions Work with data and assist in building simple ML/AI models or integrations Contribute to code quality, testing, and documentation Requirements Minimum 2 years of commercial experience with Python Initial hands-on experience with AI/ML features (e.g. working with models, APIs like OpenAI, basic ML pipelines, etc.) Understanding of software development best practices Experience working with APIs and backend services Good problem-solving skills and willingness to learn in the AI space Nice to have Experience with libraries/frameworks such as: TensorFlow, PyTorch, scikit-learn Familiarity with LLMs, NLP, or Generative AI Experience with cloud platforms (AWS, GCP, Azure) Basic knowledge of data engineering concepts We offer Opportunity to work on real AI-driven products Exposure to modern AI technologies and tools Supportive team and learning environment