Senior Data Scientist (AI Engineering Focus)

🏢 Summary: Senior Python Software Developer role focused on building and optimizing AI and machine learning solutions for scalable automotive claims processing systems. The position involves backend development, AI model integration, performance optimization, and collaboration with Data Scientists using modern cloud and DevOps technologies. 🗂️ Requirements: Degree in IT, physics, mathematics, or related field, 3+ years of Python development experience, Strong backend development experience, Hands-on experience with FastAPI and core Python, Basic understanding of machine learning, SQL knowledge, Experience with REST APIs, Experience with DevOps tools and CI/CD, Fluent written and spoken English 📃 Skills: Python, FastAPI, NumPy, OpenCV, AWS, SQL, GitLab, Docker, Kubernetes, Triton, REST, OpenAPI, Swagger, PyTorch, Haystack, LangChain 🏢 Description: About the project: Our client is an established market leader who has been processing over 18 million vehicle claims per year since 2002, with more than 1,000 employees worldwide. They combine AI-based processes and the latest technologies with automotive expertise. Responsibilities: - Design and implement software solutions in Python in the field of artificial intelligence and machine learning. - Conceptualize and test scalable applications and services that meet customer requirements. - Work closely with Data Scientists and Developers to integrate AI models into existing systems. - Analyze and optimize the performance of AI applications to maximize efficiency and effectiveness. - Contribute to the continuous development and improvement of development processes and methods. Requirements: - Degree in IT, physics, mathematics, or a related field, preferably complemented by a computer science degree. - Three or more years of experience in Python development. - Solid backend development experience. - Hands-on knowledge of FastAPI and core Python. - Basic understanding of machine learning and SQL. - Excellent analytical and problem-solving skills. - Ability to work independently and stay organized. - Strong teamwork skills. - Fluent written and spoken English. Technical skills: - Experience with Python, including NumPy, OpenCV, and FastAPI. - Experience with AWS ML services. - Experience with DevOps tools including GitLab CI/CD, Docker, Kubernetes, and NVIDIA Triton. - Experience with backend development technologies including REST API, OpenAPI, and Swagger. Nice-to-have: - Experience with AI frameworks. - Experience with LLM frameworks such as Haystack and LangChain. - Experience with PyTorch.

🏢 Summary: Senior Machine Learning Engineer role focused on designing, developing, and deploying advanced AI models across NLP-driven document intelligence and predictive analytics initiatives. The position covers the full ML lifecycle, including LLM pipeline design, forecasting and optimization models, and production-grade MLOps in secure on-premise environments. The role operates within an agile framework with strong emphasis on robustness, explainability, and scalable deployment. 🗂️ Requirements: 5+ years of Machine Learning Engineering experience, Proven experience deploying ML models to production, Expert-level Python proficiency, Hands-on experience with PyTorch, TensorFlow, Scikit-learn, Strong experience with transformer architectures (BERT, GPT, Llama), Experience with NLP frameworks such as Hugging Face or LangChain, Experience with Docker and Kubernetes, Experience with MLflow or similar MLOps tools, Experience building data preprocessing pipelines for structured and unstructured data, Experience designing time-series forecasting models, Experience building classification and anomaly detection models, Ability to implement optimization algorithms, Experience working in agile environments 📃 Skills: Python, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, BERT, GPT, Llama, HuggingFace, LangChain, Docker, Kubernetes, MLflow, Kubeflow, SQL, NLP, LLM, RAG 🏢 Description: N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact. We are looking for a Senior Machine Learning Engineer to lead the development and deployment of advanced AI models. In this role, you will be responsible for the end-to-end lifecycle of our machine learning systems, from architectural design and data preprocessing to model training, optimization, and production deployment. You will work at the intersection of generative AI and traditional machine learning, building the engines that power two strategic AI initiatives spanning NLP-based document intelligence and predictive analytics. Operating within a structured agile delivery model with formal review gates, you will ensure our models are not just accurate, but also robust, explainable, and deployable within highly secure, on-premise environments. Key Responsibilities: LLM and NLP Pipelines Design and fine-tune Large Language Model (LLM) pipelines to interpret complex regulatory texts (e.g. standards, building codes) and extract structured rules. Convert natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by downstream compliance engines. Implement RAG (Retrieval-Augmented Generation) architectures to enable semantic querying of technical documentation and historical project data. Optimize prompt strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining. Predictive and Analytical Models (Supply Chain) Develop time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals. Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors. Design algorithms for multi-objective optimization(e.g., balancing cost vs. lead time vs. risk) to support procurement decision-making. MLOps and Productionization Containerize models using Docker/Kubernetes and deploy them into secure, on-premise inference environments. Build automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability. Optimize model inference latency and resource usage (e.g., quantization, distillation) to run efficiently on available hardware. Implement monitoring systems to track model drift and performance in production, establishing feedback loops for continuous improvement. Requirements: 5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments. Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy). Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain). Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow). Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data. Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations. Ability to quickly learn and apply ML techniques to specialized domains like engineering, supply chain, or other highly regulated industries. Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements. Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.

🏢 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 Data Scientist role focused on building and operating real-time, AI-driven decisioning systems that directly impact user experience and conversion rates. The position involves developing and deploying production-grade machine learning models with strict low-latency requirements and contributing to personalization, experimentation, and recommendation systems. It combines hands-on ML engineering with experimentation, causal analysis, and large-scale data processing in a business-facing environment. 🗂️ Requirements: 7+ years commercial experience in Data Science with production ML focus, Strong experience deploying and maintaining production ML models, Experience with real-time systems and low-latency constraints, Proficiency in Python and SQL, Hands-on experience with gradient boosting methods, Experience with recommendation systems and uplift modeling, Strong knowledge of A/B testing and causal inference, Experience building feature engineering pipelines at scale, Experience with Apache Spark or PySpark, Cloud platform experience (AWS preferred), Familiarity with LLMs and GenAI for personalization 📃 Skills: Python, SQL, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, PySpark, Spark, AWS, Databricks, NLP, LLM, GenAI 🏢 Description: We are looking for a Senior Data Scientist to join a Growth Alliance team focused on AI-driven decisioning and user-facing machine learning systems. This role is suited for a technically strong data scientist who is equally comfortable working with business stakeholders and operating production ML systems at scale. About the Project: This is a high-impact role working directly on systems that influence end-user experience and conversion. You will operate in a real-time environment with strict low-latency requirements (<40 ms), contributing to a shift toward AI-driven decisioning aimed at improving product performance and increasing conversion rates. The work spans production ML pipelines, experimentation, and personalization, not just research or experimentation in isolation. Responsibilities: Design, develop, and deploy production machine learning models with real-time constraints; Build and maintain recommendation systems, uplift models, and contextual bandit frameworks; Conduct A/B testing, causal inference analyses, and statistical hypothesis testing; Develop and maintain feature engineering pipelines at scale using PySpark / Apache Spark; Monitor and validate deployed models to ensure performance and reliability; Collaborate closely with business stakeholders to challenge assumptions and define the right problems; Contribute to generative AI and LLM-based personalization initiatives; Work with decisioning platforms, personalization engines, and Martech integrations. Qualifications: 7+ years of commercial experience in Data Science with a strong production ML focus; Proficiency in Python (NumPy, Pandas, Scikit-learn) and SQL; Hands-on experience with gradient boosting methods (XGBoost, LightGBM); Experience with recommendation systems, clustering, NLP, and uplift modeling; Solid background in A/B testing frameworks, causal inference, and statistical modeling; Experience with feature engineering and production ML pipelines at scale; Cloud platform experience, preferably AWS; Familiarity with LLMs, prompt engineering, and GenAI for content personalization; Strong communication skills and ability to work in a highly business-facing environment; Databricks experience is a nice to have. Recruitment Process: Initial interview with our recruitment team; Interview with the hiring manager; Live Coding Assessment; Meeting with the Project Manager. Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.

🏢 Summary: Senior Software Engineer role focused on designing and developing a robust Kotlin-based framework for configuring and managing AI agents. The position involves building a scalable, high-performance platform using reactive and distributed system principles. The engineer will ensure code quality, optimize performance, and maintain technical documentation. 🗂️ Requirements: 5+ years experience with Kotlin or Java, Strong experience with Spring Framework, Experience with reactive programming (Project Reactor), Knowledge of REST, GraphQL, gRPC, Experience with distributed systems, Experience with tracing, metrics, monitoring practices, Experience building frameworks or platforms, Proficiency with Maven or similar build tools, Experience with NoSQL databases 📃 Skills: Kotlin, Java, Spring, Reactor, REST, GraphQL, gRPC, DistributedSystems, Maven, NoSQL, Tracing, Monitoring, Metrics 🏢 Description: N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world. We are looking for talented Senior Software Engineer to join our AI project in Europe. Responsibilities: Design and develop a robust and extensible Kotlin framework and platform for configuring and managing AI agents Write clean, maintainable, and efficient code that complies with our coding standards Ensure the performance, quality, and responsiveness of the framework/platform Identify and correct bottlenecks and errors Help to maintain code quality, organization, and automatization. Create and maintain technical documentation for the framework/platform Requirements: At least 5 years of proficiency in Kotlin or Java Deep experience with the Spring Framework Reactive tools experience (Project Reactor) Knowledge of different communication protocols such as REST, GraphQL, gRPC Experience with distributed systems Familiarity with tracing, metrics and monitoring best practices Experience of creating frameworks and platform for other developers Proficiency in Maven or similar tools Familiarity with NoSQL databases Very good spoken and written knowledge of English language (C1) Nice to have: Familiarity with GenAI, AI agents, machine learning, and natural language processing concepts is a plus Experience with MCP, A2A, RAG is a big plus Experience with event-driven architecture Experience with Docker and Kubernetes Python experience is nice to have BSc or MSc in Computer Science, Engineering or relevant field

🏢 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: 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: Senior Front-End Engineer role focused on building core components of an AI-powered document processing and workflow automation platform for a global financial services organization. The position combines strong React/TypeScript front-end development with full-stack integration in a cloud-native environment. You will contribute to architecture, performance, security, and integration with AI-driven services. 🗂️ Requirements: 6+ years software engineering experience with strong front-end focus, Strong proficiency in React and TypeScript, Solid understanding of front-end architecture and state management, Experience integrating REST APIs, microservices, or event-driven systems, Experience with relational or NoSQL databases, Experience with cloud platforms (GCP, AWS, or Azure), Familiarity with CI/CD pipelines and Docker, Experience with Git and modern DevOps tools, Understanding of performance, scalability, and security principles, Experience working in agile cross-functional teams 📃 Skills: React, TypeScript, JavaScript, HTML, CSS, REST, Microservices, Python, FastAPI, Flask, Django, PostgreSQL, MySQL, MongoDB, Firestore, GCP, AWS, Azure, Docker, Git, CI/CD, PubSub, WebSockets, OAuth2, JWT, IAM, VertexAI, Gemini, LangChain 🏢 Description: (4579) N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact. Position Overview: Our client is a global UK-based financial services and investment banking organization developing an AI-powered document processing and automation platform used across multiple business units. The platform enables large-scale data processing, workflow automation, intelligent document recognition, and modern digital experiences for internal consumers across the banking group. We are looking for a Senior Front-End Engineer with solid full-stack capability to join a cross-functional engineering team building core components of the AI-driven document processing automation platform Key Responsibilities Build modern UI components and front-end features using React and TypeScript Develop reusable component libraries, design systems, hooks, and state management patterns. Work with product and design teams to translate workflows into high-quality user experiences. Integrate UIs with backend APIs, real-time events, and AI-driven document workflows. Ensure front-end performance, accessibility, responsiveness, and frontend security best practices. Collaborate with GenAI engineering teams to integrate document-processing functionality. Work with Google Cloud services such as Cloud Run, Cloud Functions, Pub/Sub, Cloud Storage. Participate in architectural discussions and technical decision-making across the platform. Write automated tests and contribute to CI/CD, code quality, and secure development practices. Requirements 6+ years of experience in software engineering with significant front-end focus. Strong proficiency in React and TypeScript Solid understanding of front-end architecture, state management, component lifecycles, and rendering models. Experience in consuming and integrating REST APIs, microservices, or event-driven systems. Experience with Python frameworks is a strong plus (FastAPI, Flask, Django). Experience with relational and/or NoSQL databases (PostgreSQL, MySQL, MongoDB, Firestore). Experience with cloud-native environments (GCP preferred; AWS/Azure acceptable). Familiarity with CI/CD pipelines, Docker, Git, and modern DevOps tooling. Strong software engineering principles: reliability, scalability, performance, security. Experience working in agile cross-functional teams on complex, multi-team products. Strong communication skills for working with technical and non-technical stakeholders. Nice to Have Experience integrating with AI/ML or GenAI-driven features. Experience with Vertex AI, Gemini, LangChain, or LLM-based services. Familiarity with event-driven systems, WebSockets, or Pub/Sub. Experience building internal tools, dashboards, or workflow automation systems. Knowledge of authentication and authorization standards (OAuth2, JWT, SSO, IAM). Understanding of OCR, document processing, or enterprise workflow products.

🏢 Summary: Senior Software Engineer role focused on building and scaling a high-performance, AI-supported trade management platform using Rust and C#. The position involves designing distributed, event-driven systems with strong emphasis on performance, scalability, and reliability. The engineer will own solutions end-to-end and optimize cloud-based backend systems. 🗂️ Requirements: 5+ years of software engineering experience, Strong system design knowledge, Strong understanding of concurrency, Strong understanding of performance optimization, Hands-on Rust experience in production, Familiarity with C#/.NET, Experience with distributed systems, Experience with cloud platforms (preferably AWS), Practical use of AI tools in development workflows 📃 Skills: Rust, C#, NET, AWS, Kafka, RabbitMQ, AI, DistributedSystems, Concurrency, PerformanceOptimization 🏢 Description: Senior Software Engineer C# (AI-driven systems) We are looking for an experienced Software Engineer who combines strong system design skills with a modern, AI-supported development approach. This role focuses on building and scaling a high-performance trade management platform, primarily in Rust, with some exposure to C#/.NET. You will work on distributed, event-driven systems processing large volumes of data, with a strong focus on performance, scalability, and reliability. Key Responsibilities Develop and optimize high-performance backend systems Design and maintain scalable distributed services Use AI tools to accelerate development, testing, and debugging Own solutions end-to-end, from design to production Improve system performance and cloud efficiency Requirements 5+ years of experience in software engineering Strong fundamentals in system design, concurrency, and performance Hands-on experience with Rust (production level) Familiarity with C#/.NET Experience with distributed systems and cloud (preferably AWS) Practical use of AI tools in development workflows Nice to have Experience with messaging systems (Kafka, RabbitMQ, etc.) Exposure to financial systems or trading environments