Senior GenAI Engineer

🏢 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: Senior AI Engineer role focused on building and deploying production-grade AI solutions using Python, FastAPI, Azure, Generative AI, RAG, and agentic frameworks in a hybrid work model. The position includes backend architecture, AI pipeline development, MLOps ownership, and mentoring responsibilities. 🗂️ Requirements: 6–10 years of software engineering experience, Strong AI/ML engineering background, Expertise in Python, Expertise in FastAPI, Experience with LLMs, Experience with RAG pipelines, Experience with vector databases, Hands-on experience with agentic AI frameworks, Production experience with Azure cloud services, Knowledge of MLOps, Experience with Docker, Experience with Kubernetes, Experience with CI/CD 📃 Skills: Python, FastAPI, Azure, LLMs, RAG, Pinecone, Milvus, LangChain, LangGraph, AutoGen, CrewAI, Docker, Kubernetes, CI/CD, MLOps, AKS 🏢 Description: Location: Wroclaw, Poland (Hybrid: 3 days/week in-office) Experience: 6–10 years About the Role We are looking for a Senior AI Engineer to design, develop, and deploy production-grade AI solutions using Python, FastAPI, and Azure, with a strong focus on Generative AI, LLMs, RAG, and agentic frameworks. Key Responsibilities Architect and implement scalable backend services with Python and FastAPI . Build and optimize RAG pipelines using vector databases (e.g., Pinecone, Milvus, Azure Cognitive Search). Develop autonomous agents using agentic AI frameworks (LangChain, LangGraph, AutoGen). Deploy and manage AI workloads on Azure (Azure ML, AKS, OpenAI Service). Own the full ML lifecycle: experimentation, versioning, CI/CD, and monitoring. Mentor junior engineers and drive technical best practices. Required Skills 6–10 years of software engineering experience, with strong focus on AI/ML. Expert in Python and FastAPI . Deep experience with LLMs , RAG , and vector databases . Hands-on experience with agentic frameworks (LangChain, CrewAI, etc.). Production experience with Azure cloud services. Strong understanding of MLOps, containerization (Docker/Kubernetes), and CI/CD.

🏢 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: The offer is for a Senior Python AI Engineer to build and deploy a GenAI agent that learns from past RFP/RFI responses and accelerates new request handling. The role focuses on developing agentic AI solutions with RAG pipelines and running them reliably on AWS. You will design, implement, and maintain scalable, production-grade GenAI services within an Agile team. 🗂️ Requirements: 3+ years of Python development experience, Hands-on experience with LangChain, LangGraph or similar agent frameworks, Experience with LLM/GenAI projects, Understanding of agentic design patterns (tools, planners, memory), Knowledge of vector databases and embeddings, Experience with prompt engineering, Proficiency with Docker, Experience with Git-based CI/CD, Experience with automated testing, Experience deploying solutions on AWS, Upper-Intermediate (B2) English or higher 📃 Skills: Python, LangChain, LangGraph, LLM, GenAI, RAG, AWS, Docker, Git, CI/CD, VectorDB, Embeddings, Prompting, Serverless, APIs 🏢 Description: We are seeking a Senior Python AI Engineer who has hands-on experience with agentic AI frameworks (LangChain, LangGraph, etc.) and knows how to run GenAI workloads on AWS. You will join the team building a GenAI agent that learns from past RFP/RFI responses and helps teams answer new requests faster. Responsibilities Build Python services that power the GenAI agent using LangChain, LangGraph, or similar libraries Create retrieval-augmented generation (RAG) flows that pull the right context and streamline LLM responses Run the solution on AWS using containers, serverless functions, or managed AI services Instrument logging, monitoring, and guardrails to keep the agent reliable and safe Ensure the ingestion and use of RFP/RFI data follows healthcare data policies Collaborate with product, data science, and business teams to make sure the agent solves real problems Document code, APIs, and deployment steps so others can maintain and extend the solution Work within an Agile team and contribute to planning, demos, and retros Requirements 3+ years of Python development experience, with a recent focus on LLM or GenAI projects Hands-on experience with LangChain, LangGraph, or comparable agent frameworks Understanding of agentic design patterns and how to wire tools, planners, and memory together Knowledge of vector databases, embeddings, and prompt engineering Proficiency in Docker, Git-based CI/CD, and automated testing Solid communication skills and the ability to work with technical and non-technical stakeholders English language proficiency at an Upper-Intermediate level (B2) or higher Nice to have Familiarity with healthcare payer workflows, especially RFP/RFI processes Experience integrating with CRMs/workflow tools like Salesforce or ServiceNow Exposure to responsible AI, human-in-the-loop review, or safety tooling AWS or Python certifications We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Oferta dotyczy długoterminowej pracy jako AI Engineer lub Senior AI Engineer przy budowie i skalowaniu rozwiązań opartych o Generative AI, LLM oraz AI Agents. Rola obejmuje projektowanie architektury AI, implementację RAG, rozwój API i pipeline’ów MLOps oraz integrację modeli AI z systemami biznesowymi. Praca odbywa się głównie zdalnie w modelu B2B lub UoP, w niewielkim zespole realizującym projekty produkcyjne. 🗂️ Requirements: Minimum 3 lata doświadczenia komercyjnego jako AI Engineer, ML Engineer lub pokrewna rola, Bardzo dobra znajomość Python, Znajomość LangChain, LangGraph, LlamaIndex lub podobnych frameworków, Doświadczenie z rozwiązaniami RAG, Znajomość baz wektorowych, Umiejętność projektowania i budowy REST API, Doświadczenie z Docker, Doświadczenie z AWS, Azure lub GCP, Znajomość Git, Znajomość dobrych praktyk Software Engineering, Umiejętność pracy w Agile, Język angielski na poziomie minimum B2+/C1- 📃 Skills: Python, LLM, OpenAI, Anthropic, Gemini, Llama, LangChain, LangGraph, CrewAI, AutoGen, RAG, FastAPI, Docker, Kubernetes, AWS, Azure, GCP, PyTorch, HuggingFace, MLflow, Airflow, Redis, PostgreSQL, LlamaIndex, Qdrant, Pinecone, Milvus, Weaviate, ChromaDB, REST, Git, Agile, SemanticKernel, MCP, LoRA, QLoRA, CI/CD, MLOps, vLLM, Ollama, TGI 🏢 Description: W ITLT pomagamy naszym partnerom budować rozwiązania, które jeszcze kilka lat temu wydawały się niemożliwe. Pracujemy z organizacjami rozwijającymi produkty oparte o Generative AI, LLM, AI Agents oraz nowoczesne platformy Machine Learning. Współtworzymy rozwiązania od fazy Proof of Concept, przez produkcyjne wdrożenia, aż po skalowanie środowisk AI obsługujących tysiące użytkowników Aktualnie poszukujemy osób na stanowisko: AI Engineer i Senior AI Engineer Konkrety: Forma współpracy: B2B lub UoP. Jesteśmy w pełni otwarci na Twoją propozycję - wystarczy wpisać odpowiednią kwotę w formularzu aplikacyjnym Miejsce pracy: Zapewniamy dużą swobodę pracy zdalnej, przy czym zapraszamy od czasu do czasu do naszego warszawskiego biura Wymiar pracy: Full-time Zespół: 6-8os. Proces rekrutacji: 1-etapowy (spotkanie zdalne via MS Teams). Sporadycznie możliwe dodatkowe krótkie spotkanie - połączone z decyzją Szacowany czas trwania projektu: Długoterminowy/bezterminowy Tematy na projekcie: Python, LLM (OpenAI, Anthropic, Gemini, Llama), LangChain, LangGraph, CrewAI, AutoGen, RAG, Vector Databases, FastAPI, Docker, Kubernetes, AWS, Azure, GCP, PyTorch, Hugging Face, MLflow, Airflow, Redis, PostgreSQL Do Twoich głównych obowiązków na tym stanowisku należeć będzie: Budowa i rozwój aplikacji opartych o Generative AI Tworzenie agentów AI wspierających procesy biznesowe Projektowanie architektury rozwiązań LLM Implementacja RAG oraz integracja z bazami wektorowymi Fine-tuning i optymalizacja modeli Integracja modeli AI z istniejącymi systemami Budowa API oraz mikroserwisów wspierających rozwiązania AI Rozwój pipeline'ów Machine Learning i MLOps Optymalizacja kosztów oraz wydajności rozwiązań AI Współpraca z zespołami Data Science, Software Engineering oraz Cloud Ta oferta będzie idealna dla Ciebie, jeśli posiadasz: Minimum 3 lata doświadczenia komercyjnego jako AI Engineer, ML Engineer lub pokrewnej roli Bardzo dobrą znajomość Pythona Praktyczną znajomość frameworków takich jak LangChain, LangGraph, LlamaIndex lub podobnych Doświadczenie z rozwiązaniami RAG Znajomość baz wektorowych (Qdrant, Pinecone, Milvus, Weaviate, ChromaDB) Umiejętność projektowania i budowy REST API Doświadczenie z Docker oraz środowiskami Cloud (AWS, Azure lub GCP) Znajomość Git oraz dobrych praktyk Software Engineering Umiejętność pracy w środowisku Agile Język angielski (przynajmniej na poziomie B2+/C1- Mile widziana znajomość: AI Agents (CrewAI, AutoGen, Semantic Kernel) MCP (Model Context Protocol) Fine-tuning modeli Open Source LoRA / QLoRA Hugging Face PyTorch Kubernetes CI/CD MLOps Prompt Engineering Observability dla systemów AI Znajomość inferencji modeli lokalnych (vLLM, Ollama, TGI) Warto do nas dołączyć, ponieważ oferujemy: Dużą swobodę pracy zdalnej Długofalowe stabilne zatrudnienie Szansę na uczestniczenie w kluczowych projektach dla dużej firmy działającej w bardzo stabilnym sektorze Atrakcyjne wynagrodzenie (adekwatne do umiejętności i doświadczenia) Benefity (Lux Med, MultiSport...) W razie pytań pingnij śmiało na Linkedin'ie do Kuby

🏢 Summary: AI Engineer role focused on developing and enhancing ML and GenAI/LLM-based solutions for fraud detection, anomaly detection, and transaction analytics in the banking sector. The position involves building scalable applications, creating and optimizing machine learning models, and analyzing large-scale data sets. Work is primarily remote with periodic onsite collaboration. 🗂️ Requirements: Higher education degree in ComputerScience, Mathematics, Physics or related field, Minimum 3 years of commercial experience in DataScience, Experience in building and evaluating MachineLearning models, Hands-on experience with LLM and GenAI models and Embeddings, Strong programming skills in Python 📃 Skills: Python, MachineLearning, DataScience, LLM, GenAI, Embeddings, Spark, Hadoop, Hive, Azure, FastAPI, Spring, REST, PowerBI, CICD 🏢 Description: AI Engineer (GenAI, LLM) Na potrzeby projektów z obszaru dużych modeli językowych LLM/Gen AI poszukujemy osób na stanowisko AI Engineer. Obecnie nasz klient - lider innowacyjnych rozwiązań bankowych pracuje nad autorskim systemem do detekcji fraudów, detekcji anomalii oraz analityki w transakcjach klientów. Lokalizacja: Praca zdalna + praca zespołowa z biura w Warszawie (2x w miesiącu) Główne zadania Rozwój aplikacji, które dotykają milionów klientów każdego dnia Pisanie kodu z dbałością o każdy szczegół Tworzenie nowych modeli ML lub rozwój już istniejących Rozwiązywanie problemów, z którymi nie radzą sobie inne zespoły Analiza TB danych w celu poprawy jakości rozwiązań - oferujemy dużą przestrzeń do pracy kreatywnej Oczekiwania Wykształcenie wyższe na kierunku informatyka, fizyka, matematyka, lub pokrewnym (warunek konieczny) Min. 3 lata doświadczenia komercyjnego w zakresie tworzenia rozwiązań Data Science Wiedza z zakresu tworzenia modeli uczenia maszynowego oraz ich ewaluacji Doświadczenie z dużymi modelami językowymi (LLM), embedingami oraz modelami GenAI Doświadczenie w programowaniu z wykorzystaniem Python Ciągła chęć rozwoju, odpowiedzialność, kreatywność oraz pomysłowość Biegła znajomość j. polskiego, dobra znajomość j. angielskiego Mile widziane: doświadczenie przy pisaniu aplikacji RESTowych (np. Spring albo FastAPI) Doświadczenie w pracy z narzędziami Big Data: Spark, Hadoop, Hive etc. doświadczenie w pracy w chmurze Azure doświadczenie w pracy z PowerBi doświadczenie w pracy z narzędziami CI/CD Oferujemy Stałe wsparcie osobistego agenta , dbającego o Twoją ciągłość projektową, kontakt z klientem, niezbędne formalności, komfort pracy oraz rozwój Stabilny projekt i długofalową współpracę w oparciu o umowę o pracę Rozwój zawodowy nie tylko podczas projektu – możesz zaangażować się w przekazywanie wiedzy innym w ramach oferty 7N Services kierowanej do klientów 7N Dostęp do 7N Learning & Development – platformy rozwojowo-edukacyjnej z webinarami, biblioteką artykułów i raportów branżowych oraz zaproszeniami na wydarzenia rozwojowe – techniczne, biznesowe oraz life-stylowe Udział w wybranych eventach organizowanych przez klienta (wyjazdy integracyjne, spotkania świąteczne) oraz 7N (eventy sportowe) Relacje i dostęp do wiedzy najbardziej doświadczonych ekspertów IT na rynku Narzędzia niezbędne do świadczenia usług Pracę hybrydową z przewagą pracy zdalnej z dowolnego miejsca w Polsce (90%) Spotkanie zespołowe w biurze klienta w Warszawie raz na 2 tygodnie Pakiet benefitów zaplanowany od A do Z, czyli dofinansowanie do opieki medycznej, ubezpieczenia na życie, karty sportowej dla Ciebie i Twoich bliskich, a także zniżki do sklepów w Polsce i za granicą.

🏢 Summary: Remote EU-based Senior AI and Python Engineer role focused on designing, deploying, and optimizing autonomous AI agents and multi-agent systems. The position involves integrating LLM-powered solutions with enterprise systems, improving performance and safety, and collaborating across teams to embed AI capabilities into products. Candidates need strong Python, AI/ML engineering, and cloud platform expertise with hands-on experience in modern AI agent frameworks. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, AI, or related field, 5+ years of AI/ML engineering experience, Experience with agent-based systems, Hands-on experience with LangChain, LangGraph, or OpenAI Agents SDK, Proficiency in Python, Knowledge of asyncio and orchestration patterns, Understanding of LLM capabilities, Experience with AWS, Azure, or GCP, Experience deploying LLM agents, System integration experience, Fluent English, Legal right to work within the European Union 📃 Skills: Python, LangChain, LangGraph, OpenAI, asyncio, AWS, Azure, GCP, LLM 🏢 Description: Unleash the Future of Autonomous Intelligence — Drive the Development of Next-Generation AI Agents! Remote opportunity in the EU—work from anywhere within the region! As a Senior AI and Python Engineer, you will be working for our client, a leader in AI innovation, dedicated to creating transformative autonomous systems. Join a pioneering team to design, develop, and deploy sophisticated AI agents capable of complex reasoning, dynamic planning, and autonomous execution that push technological boundaries and redefine industry standards. Your main responsibilities: Lead the design and deployment of single and multi-agent systems using advanced frameworks. Architect and optimize agents for complex workflows and multi-step tasks. Integrate AI agents with external tools, APIs, and enterprise systems to ensure seamless functionality. Implement strategies for performance enhancement, reliability, and ethical considerations. Manage agent lifecycle, ensuring safe and responsible behavior. Keep abreast of the latest AI research and incorporate innovations into solutions. Collaborate with cross-functional teams to embed AI capabilities into core products. Document system architecture and operational procedures to support scalability and maintenance. You're ideal for this role if you have: Bachelor’s or Master’s degree in Computer Science, AI, or a related field. 5+ years of experience in AI/ML engineering, specializing in agent-based systems. Hands-on experience with frameworks like LangChain, LangGraph, or OpenAI Agents SDK. Proficiency in Python, including asyncio and orchestration patterns. Strong understanding of LLM capabilities and cloud platforms (AWS, Azure, GCP). Proven success in deploying LLM agents and system integration. Excellent problem-solving skills and the ability to communicate complex ideas effectively. It is a strong plus if you have: Certifications or experience in cloud architecture and security. Knowledge of ethical AI practices and safety protocols. Language required for the role: Fluent English, with excellent communication skills. Eligibility to work in Europe: Only candidates with a legal right to work within the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data. You can also send your application via email at cv-recruitment@itdsportugal.com.

🏢 Summary: The role focuses on building and evolving core platform services to support engineering teams, emphasizing scalable cloud-native solutions, developer experience, and automation. It involves designing shared services, advancing CI/CD and Infrastructure as Code practices, and integrating AI-powered tools and LLM-based solutions. The position also promotes DevOps and SRE standards to ensure reliability and operational excellence in production environments. 🗂️ Requirements: 8+ years of experience delivering production-grade software solutions, Strong proficiency in Python, Experience with Kubernetes and containerized environments, Experience with distributed systems, Knowledge of REST and gRPC service development, Experience with cloud-native architectures, Hands-on experience with Infrastructure as Code tools, Familiarity with AI tooling and LLM-based applications, Ability to support production systems and incident response 📃 Skills: Python, Kubernetes, Docker, REST, gRPC, Terraform, CI/CD, LLM, AI, DevOps, SRE, Cloud, Automation 🏢 Description: We are looking for a Senior Platform Engineer to help build and evolve the core technology platforms that support our engineering organization. This role focuses on developing scalable software solutions, improving developer experience, and driving cloud-native engineering practices across the business. Working closely with engineering, cloud, and operations teams, you will contribute to platform architecture, automation initiatives, and the adoption of modern development and reliability practices. Key Responsibilities • Design and maintain shared platform services and engineering tools used across multiple teams. • Develop and enhance internal platforms, including authentication, developer tooling, and infrastructure services. • Build AI-powered solutions leveraging LLMs, intelligent agents, and automation technologies. • Contribute to engineering standards, architectural guidelines, and reusable frameworks. • Improve software delivery through CI/CD, automation, and Infrastructure as Code. • Promote DevOps and SRE practices, including observability, monitoring, and operational excellence. • Support production systems through incident response and reliability improvements. Required Qualifications • 8+ years of experience delivering software solutions in production environments. • Strong programming skills in Python; experience in other languages like Java, C#, C++, Go or others, nice to have • Experience with Kubernetes, containers, and distributed systems. • Knowledge of REST and gRPC service development. • Experience with solution architecture and cloud-native technologies. • Familiarity with AI tooling, agent-based frameworks, and LLM-powered applications. • Hands-on experience with Infrastructure as Code tools such as Terraform. • Strong communication and technical documentation skills.

🏢 Summary: Tech Lead AI responsible for designing and scaling GenAI systems based on Python, leading a team in building LLM-powered solutions such as chatbots, AI agents, and RAG systems. The role focuses on architecture, optimization, and integration of AI solutions with scalable backend and cloud environments. It combines hands-on development of advanced AI systems with technical leadership and strategic technology direction. 🗂️ Requirements: Minimum 6 years in software engineering, At least 2 years in Lead/Staff/Principal/Manager role, Expertise in Python, Experience with ML/AI frameworks, Experience building and optimizing LLM systems, Experience with chatbots, AI agents and RAG, Knowledge of scalable APIs and distributed systems, Experience with cloud platforms, Experience with Docker and Kubernetes, Experience with fine-tuning AI models, Knowledge of LangChain and LlamaIndex, Experience with MLOps and CI/CD for AI, Ability to design system architecture and conduct code reviews 📃 Skills: Python, Django, FastAPI, Flask, TensorFlow, PyTorch, HuggingFace, LLM, RAG, LangChain, LlamaIndex, OpenAI, Anthropic, Mistral, LLaMA, AWS, GCP, Azure, Docker, Kubernetes, MLOps, CI/CD, Prompting 🏢 Description: O roli Szukamy Tech Leada AI z silnym doświadczeniem w Pythonie , który będzie odpowiedzialny za architekturę i rozwój systemów opartych na GenAI . Osoba na tym stanowisku pokieruje zespołem inżynierów, wdrażając nowoczesne rozwiązania oparte na LLM, chatbotach, agentach AI i systemach RAG . Twoim zadaniem będzie tworzenie, optymalizacja i skalowanie systemów AI , a także aktywna współpraca z zespołami produktowymi, badawczymi i biznesowymi. Rola wymaga silnego technicznego leadershipu , strategicznego myślenia oraz umiejętności przekładania celów biznesowych na efektywne rozwiązania inżynieryjne . Twoje zadania 🔹 Projektowanie i rozwój systemów GenAI: Tworzenie architektury i infrastruktury AI opartych na Pythonie. Optymalizacja wydajności i skalowalności LLM, chatbotów, agentów AI oraz systemów RAG . Integracja rozwiązań AI z systemami backendowymi i produktami cyfrowymi. 🔹 Zarządzanie zespołem i technologią: Techniczne prowadzenie zespołu programistów, zapewnienie code quality i best practices . Mentoring i rozwój zespołu w zakresie technologii GenAI. Definiowanie roadmapy technologicznej i priorytetów zespołu. 🔹 Innowacje i strategia: Badanie i wdrażanie najnowszych frameworków oraz modeli LLM (np. OpenAI, Anthropic, Mistral, LLaMA). Tworzenie customowych modeli AI oraz optymalizacja procesów inferencji. Eksploracja możliwości fine-tuningu LLM oraz strategii prompt engineeringu . 🔹 Współpraca z biznesem i produktami: Ścisła współpraca z zespołami data science, ML i produktowymi . Konsultowanie architektury i strategii AI z interesariuszami biznesowymi. Tworzenie AI-driven rozwiązań , które realnie wpływają na użytkowników. Czego oczekujemy? Min. 6 lat doświadczenia w inżynierii oprogramowania , w tym 2+ lat jako Lead/ Staff/ Principal lub Manager. Ekspertyza w Pythonie (Django, FastAPI, Flask) oraz frameworkach ML/AI (TensorFlow, PyTorch, Hugging Face). Doświadczenie w tworzeniu i optymalizacji LLM, chatbotów, agentów AI, RAG . Znajomość architektur skalowalnych API i systemów rozproszonych . Doświadczenie w pracy z chmurami (AWS, GCP, Azure) i konteneryzacją (Docker, Kubernetes). Umiejętność prowadzenia code review, architektury rozwiązań i strategii technologicznej . Świetne zdolności komunikacyjne i współpracy z różnymi działami. Doświadczenie w fine-tuningu modeli AI i strategiach retrieval-augmented generation (RAG) . Znajomość technologii LangChain, LlamaIndex, Prompt Engineering . Background w MLOps, CI/CD dla AI .