Python Developer & AI

🏢 Summary: Senior-level role focused on building AI-driven backend applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The position involves developing scalable APIs, integrating retrieval pipelines, and deploying services in cloud environments. The role combines advanced AI implementation with solid backend engineering practices. 🗂️ Requirements: 5+ years commercial experience in Python development, Strong backend engineering experience (APIs, services, integrations), Hands-on experience with LLMs, Hands-on experience with RAG implementations, Experience with Azure, AWS, or GCP, Knowledge of software development best practices 📃 Skills: Python, LLMs, RAG, Azure, AWS, GCP, APIs 🏢 Description: Senior Python AI Developer We are looking for an experienced Python Developer to join a team building modern AI-driven applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) , alongside standard backend development work. Key Responsibilities Develop and maintain backend services and APIs in Python Build AI-enabled application features using LLMs and RAG workflows Design and integrate retrieval pipelines for contextual AI responses Work with databases, external APIs, and internal systems Deploy and operate services in Azure or other cloud environments Write clean, testable, and scalable production code Requirements 5+ years of commercial experience in Python development Strong background in backend engineering (APIs, services, integrations) Hands-on experience with LLMs and RAG implementations Cloud experience with Azure , AWS, or GCP Solid understanding of software development best practices Tech Stack Python LLMs, RAG Azure (or other cloud platforms)

🏢 Summary: The role focuses on engineering production-grade AI features such as semantic search, intelligent assistants, and automated risk scoring by integrating external AI providers into a cybersecurity platform. You will own the full lifecycle from prototype to reliable, monitored production services, primarily using Python on Azure. This position emphasizes robust software engineering practices over model research or training. 🗂️ Requirements: 5+ years of professional experience building production systems in Python, Expert-level Python programming skills, Experience with ML frameworks and libraries, Proven experience shipping and operating production software, Experience integrating external APIs in production environments, Strong understanding of software architecture and design patterns, Practical experience with CI/CD pipelines, Experience with containerization using Docker, Understanding of AI/ML concepts including LLMs, embeddings, prompt engineering, RAG, Experience with unit and integration testing and mocking external services, Polish work permit, Professional proficiency in English 📃 Skills: Python, Azure, OpenAI, Anthropic, Docker, CI/CD, FastAPI, Flask, Pinecone, Weaviate, Chroma, .NET, REST, LLMs, RAG, Embeddings, Git 🏢 Description: About the Role As a Senior AI/ML Engineer you will be building AI-powered features at the core of our platform - semantic search, an intelligent assistant, automated risk scoring, and much more. We mainly integrate with external AI model providers (OpenAI, Anthropic, and others) to deliver these capabilities to our clients and internal users. This is a software engineering role, not a data science or ML research position. You won't train models from scratch or publish papers. You'll engineer production-grade systems that leverage AI to solve real cybersecurity problems. If you're a strong Python engineer excited about making AI reliable, maintainable, and impactful — we want to talk to you. We're looking for a versatile software engineer to own the journey from AI prototype to reliable production system: building robust integrations with external AI providers or fine-tuned models, standardizing our Python codebase and release pipelines, and ensuring our AI features meet the same quality bar as any other production service. What You'll Do Ship AI features end to end - from integration design through deployment to monitoring in production. You'll build and maintain Python services that power our AI-driven capabilities on Azure. Build production-ready AI / ML integrations - including retry logic, rate limiting, cost monitoring, fallback strategies, and abstraction layers that allow us to swap between model providers. Turn proofs of concept into reliable software - collaborate with our AI experts (who bring deep ML/data science expertise) to take working prototypes and engineer them into tested, documented, production-grade services. Standardize Python engineering practices - establish and evolve our code organization, testing strategies, CI/CD pipelines, and release processes for AI/ML features. Design clean service boundaries - our platform's core runs on .NET. You'll design and maintain well-defined APIs between the Python/AI layer and the rest of the system. Mentor and share knowledge - help other engineers grow their Python and AI engineering skills, and bring engineering rigor to the broader team's practices. Contribute to architecture decisions - work closely with other teams to shape how AI capabilities evolve within the platform. Who You Are Must-Haves 🔹 5+ years of professional experience building and maintaining production systems in Python. 🔹 Expert-level programming skills and proficiency with common ML frameworks and libraries. 🔹 A track record of shipping and operating software - not just building prototypes. You care about testing, monitoring, logging, and what happens after deployment. 🔹 Experience integrating external APIs in production systems - ideally AI/LLM provider APIs (OpenAI, Anthropic, Azure AI, or similar), but strong API integration experience in any domain counts. 🔹 Solid understanding of software architecture and design patterns - you have opinions about how to structure a Python project and can articulate trade-offs. 🔹 Practical knowledge of CI/CD pipelines, containerization (Docker), and modern development workflows. 🔹 A working understanding of AI/ML concepts - you know what embeddings, LLMs, prompt engineering, and RAG are. You can have a productive technical conversation with an ML specialist without needing every concept explained from scratch. 🔹 Experience with testing strategies - unit tests, integration tests, mocking external services. You instinctively write tests, not as an afterthought. 🔹 A highly adaptable, problem-solving and result-oriented mindset with the ability to work independently and take ownership in a fast-paced and dynamic environment. 🔹 Strong communication skills in English (our working language). 🔹 Willingness to learn continuously and share what you learn with the team. Nice-to-Haves 🔸 Experience with Azure cloud services. 🔸 Familiarity with FastAPI, Flask, or similar Python web frameworks. 🔸 Exposure to MLOps tooling or practices (model versioning, experiment tracking, feature stores). 🔸 Hands-on experience in Document AI / Intelligent Document Processing using traditional models and Generative AI. 🔸 Experience with vector databases (Pinecone, Weaviate, Chroma, or similar). 🔸 Any experience with .NET - helpful for cross-team collaboration, but not expected. 🔸 Background in or interest in cybersecurity as a domain. Your Team You'll join our Synapse team - a small, focused group responsible for all AI/ML capabilities within our platform. The team consists of: -> Team Leader / Architect - provides high-level architectural guidance, planning, and cross-stack delivery. -> AI / ML Engineer - deep expertise in AI/ML and data science. Your counterbalance: they bring the ML knowledge, you bring the production engineering discipline. -> AI / Backend Engineer - transitioning from .NET into AI engineering. A teammate you'll mentor and grow alongside. -> You - the person who bridges the gap between AI prototypes and reliable production systems. Why Join Us? / What We Offer: Competitive salary and benefits package. Remote work options and flexible working hours. Actual impact on the choice and shape of solutions developed. Opportunities for professional growth and development. Training and conference budget. A collaborative, innovative work environment with an iterative agile approach. The role is for six months with the possibility of extension. Both full-time and part-time cooperation are possible.

🏢 Summary: The offer is for a backend-focused AI Engineer role building a modern AI platform for business process automation and multi-agent system integration in a production-grade enterprise environment. The position centers on developing scalable Python-based services, secure API integrations, and cloud-native AI solutions using LLMs and RAG. The role involves designing robust, secure, and scalable architectures deployed on AWS or Azure with containerized infrastructure. 🗂️ Requirements: Extensive experience in backend development with Python in production environments, Hands-on experience with AI Agents, RAG, MCP, or LLM-based solutions, Experience with system integrations and API architecture, Experience with scalable cloud-based applications, Experience with AWS or Azure, Experience with Docker and Kubernetes, Experience designing secure and scalable enterprise solutions, Experience with multi-agent systems and workflow automation, Ability to conduct code reviews and mentor developers, Fluent English and Polish 📃 Skills: Python, LLM, RAG, MCP, AWS, Azure, Docker, Kubernetes, API, Microservices, Cloud, AI, Agents 🏢 Description: Additional information The project focuses on building and developing a modern AI platform supporting business process automation and the integration of intelligent agents with enterprise systems. The team is creating scalable solutions based on Python, cloud technologies, and multi-agent architecture, leveraging technologies such as LLMs, RAG, and advanced workflow automation. A key aspect of the project is designing secure integrations between AI platforms, internal systems, and external APIs within a production-grade environment. The project is delivered in an international technology-driven environment with a strong focus on innovation, high-quality architecture, and the development of cutting-edge AI solutions for a global industrial organization. You’re ideal for this role if you: Have extensive experience in backend development with Python in production environments Have hands-on experience with AI technologies such as AI Agents, RAG, MCP, or LLM-based solutions Understand system integrations, API architecture, and scalable cloud-based applications Have worked with AWS or Azure and containerized environments such as Docker and Kubernetes Are experienced in designing secure and scalable enterprise solutions Have strong problem-solving skills and can proactively remove technical blockers Enjoy working closely with cross-functional teams in an international environment Have experience mentoring developers, conducting code reviews, and promoting engineering best practices Are interested in modern AI architectures, workflow automation, and multi-agent systems Communicate fluently in English and Polish and feel comfortable working in a global setup Your day-to-day responsibilities include:​ Designing and developing scalable backend services and AI-driven integration solutions in Python Building and maintaining APIs, connectors, and middleware between AI platforms and enterprise systems Creating and optimizing multi-agent workflows and intelligent automation processes Collaborating with AI Engineers, Data Engineers, and other technical stakeholders on system architecture and integrations Integrating external AI platforms, internal tools, and cloud services into production environments Working with cloud technologies and containerized infrastructure in AWS or Azure environments Improving the quality, reliability, and performance of AI-powered solutions and LLM-based workflows Conducting code reviews, mentoring team members, and supporting engineering best practices Troubleshooting technical issues, identifying bottlenecks, and driving continuous improvements Contributing to technical documentation, architecture discussions, and innovation initiatives across the team

🏢 Summary: Oferta dotyczy roli inżyniera AI/LLM odpowiedzialnego za projektowanie i wdrażanie produkcyjnych systemów opartych na Pythonie oraz zaawansowanych architekturach LLM. Stanowisko obejmuje budowę rozwiązań RAG, orkiestrację agentów oraz przygotowanie pipeline’ów danych pod modele językowe. Rola wymaga pracy z wektorowymi bazami danych oraz zapewnienia jakości poprzez testy i ewaluację systemów niedeterministycznych. 🗂️ Requirements: Minimum 3 lata komercyjnego doświadczenia w projektowaniu i wdrażaniu systemów produkcyjnych w Pythonie, Doświadczenie w budowie zaawansowanych architektur LLM (RAG, harness engineering, orkiestracja), Praktyczna znajomość LangChain lub LlamaIndex, Znajomość wzorców projektowych i zasad Clean Code, Doświadczenie w pisaniu testów i ewaluacji systemów niedeterministycznych, Doświadczenie w Data Engineering dla LLM (ETL, parsowanie dokumentów, chunking, transformacje danych), Praca z bibliotekami do manipulacji danymi, Znajomość wektorowych baz danych i strategii chunkingu, Wykształcenie wyższe w kierunku ścisłym lub pokrewnym, Znajomość języka angielskiego na poziomie min. B2 📃 Skills: Python, LLM, RAG, LangChain, LlamaIndex, Pandas, NumPy, Qdrant, Pinecone, Chroma, ETL, Azure, GCP, AWS, Docker, Kubernetes, PyTorch, TensorFlow, C#, Go, Java, SQL, AzureDevOps 🏢 Description: Wymagania: Doświadczenie komercyjne: minimum 3 lata projektowania i wdrażania systemów w jakości produkcyjnej w Pythonie. Udokumentowane doświadczenie w budowaniu zaawansowanych architektur LLM: zaawansowany RAG, harness engineering oraz orkiestracja przy użyciu frameworków takich jak LangChain lub LlamaIndex. Znajomość wzorców projektowych, zasad Clean Code oraz pisania testów i ewaluacji dla systemów niedeterministycznych. Doświadczenie w Data Engineering pod LLM: ETL dla danych nieustrukturyzowanych (parsowanie dokumentów, chunking), transformacji oraz pracy z bibliotekami manipulacji danymi (Pandas, NumPy). Praktyczna znajomość wektorowych baz danych (np. Qdrant, Pinecone, Chroma) oraz strategii chunkingu i zarządzania metadanymi. Umiejętność przekładania skomplikowanych koncepcji AI na język korzyści biznesowych i współpraca z zespołami produktowymi. Wyższe wykształcenie (lub w trakcie) w naukach ścisłych/ilościowych (Informatyka, Matematyka, Fizyka, Ekonometria lub pokrewne) oraz znajomość języka angielskiego na poziomie min. B2. Welcome Skills: Znajomość zaawansowanych frameworków agentowych: LangGraph, CrewAI, AutoGen. Praktyka z chmurami (Azure, GCP lub AWS) oraz konteneryzacją i orkiestracją (Docker, Kubernetes). Zrozumienie klasycznego NLP oraz frameworków głębokiego uczenia (PyTorch, TensorFlow) na potrzeby utrzymania i aktualizacji istniejących komponentów. Znajomość dodatkowego języka (C#, Go, Java). Szczególnie cenimy komercyjne doświadczenie w ekosystemie .NET (C#, SQL Server, Azure PaaS) oraz budowaniu potoków CI/CD (Azure DevOps).

🏢 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 Engineer responsible for designing and developing AI applications in Python, including LLM-based and GenAI solutions, and deploying them in cloud environments. The role involves building REST APIs, integrating AI solutions with business systems, and managing AI models and chatbots. Hybrid work model with a 6-month project and possible extension. 🗂️ Requirements: Minimum 2–3 years of experience in similar role, Strong Python proficiency, Experience with LLM-based conversational applications, Experience with FastAPI and REST API development, Knowledge of SQLAlchemy and relational mapping, Experience with Alembic and database migrations, Asynchronous programming with asyncio, Experience with AI orchestration tools, Cloud deployment experience, API integration skills 📃 Skills: Python, Langchain, LangGraph, FastAPI, Pydantic, NumPy, Pandas, SQLAlchemy, Alembic, asyncio, Chainlit, n8n, Langflow, Kore.ai, LLM, Docker, Kubernetes, OAuth2, PostgreSQL, Redis, SQL 🏢 Description: Twój zakres obowiązków Projektowanie i tworzenie aplikacji AI w języku Python, w tym rozwiązań opartych na modelach językowych i bibliotekach GenAI, wdrażanie, zarządzanie i monitorowanie modeli AI, chatbotów oraz innych aplikacji w środowiskach chmurowych, integracja rozwiązań AI z systemami biznesowymi poprzez API, śledzenie najnowszych trendów w obszarze sztucznej inteligencji i technologii chmurowych, współpraca z zespołami biznesowymi i IT w celu dostarczania innowacyjnych rozwiązań. Wymagania Minimum 2-3 letnie doświadczenie w tej lub podobnej roli, bardzo dobra znajomość Python (Langchain, LangGraph, FastAPI, Pydantic, NumPy, Pandas), praktyczna znajomość narzędzi do orkiestracji AI i automatyzacji workflow (np. n8n, Langflow, Kore.ai), FastAPI - budowanie REST API, routing, dependency injection, middleware, SQLAlchemy - ORM, mapowanie relacyjne, Alembic - migracje baz danych, zarządzanie schematem, asyncio - programowanie asynchroniczne, chainlit,· doświadczenie w tworzeniu aplikacji konwersacyjnych opartych na LLM, myślenie analityczne i umiejętność interpretacji danych, skuteczna komunikacja – tłumaczenie złożonych zagadnień technicznych w sposób zrozumiały dla osób nietechnicznych, umiejętność pracy zespołowej i adaptacji do zmieniających się warunków. Mile widziane Znajomość Docker/Kubernetes, Domain-Driven Design (DDD) – agragaty, repozytoria, serwisy, OAuth2, wiedza z zakresu baz danych SQL, PostgreSQL, Redis. Praca hybrydowa, minimum 1 dzień w miesiącu w biurze w Warszawie Start: ASAP

🏢 Summary: The offer is for a Backend .NET Developer responsible for building and maintaining robust backend systems while supporting full software development lifecycle and DevOps practices. The role involves working in Agile teams, ensuring high performance, scalability, and seamless integration of applications. The position also emphasizes containerization and cloud-based solutions using Azure. 🗂️ Requirements: Proven experience with .NET development, Strong knowledge of Docker, Strong knowledge of Kubernetes, Familiarity with Microsoft Azure, Experience with Azure DevOps Server, Experience working in Agile environments 📃 Skills: .NET, Docker, Kubernetes, Azure, AzureDevOpsServer, Agile, DevOps, Microservices 🏢 Description: Main Responsibilities Design, develop, and maintain robust backend solutions. Collaborate across teams to ensure seamless software integration. Participate in the full software development lifecycle. Implement DevOps practices for continuous integration and delivery. Optimize application performance and scalability. Review and improve code quality through peer reviews. Key Requirements Proven experience with .NET development. Strong knowledge of Docker and Kubernetes . Familiarity with Microsoft Azure and Azure DevOps Server . Experience working in Agile environments . Strong problem-solving skills. Nice to Have Experience with microservices architecture . Knowledge of additional programming languages. Familiarity with front-end technologies.

🏢 Summary: The offer is for a Backend .NET Developer responsible for building and maintaining scalable backend solutions within a DevOps-driven environment. The role involves full software development lifecycle participation, cloud integration, and performance optimization. The position requires collaboration in Agile teams and ensuring high code quality and seamless deployment processes. 🗂️ Requirements: Proven experience with .NET development, Strong knowledge of Docker, Strong knowledge of Kubernetes, Familiarity with Microsoft Azure, Experience with Azure DevOps Server, Experience working in Agile environments, Experience implementing CI/CD practices, Ability to optimize application performance and scalability 📃 Skills: .NET, Docker, Kubernetes, Azure, AzureDevOps, CI/CD, Agile 🏢 Description: Main Responsibilities Design, develop, and maintain robust backend solutions. Collaborate across teams to ensure seamless software integration. Participate in the full software development lifecycle. Implement DevOps practices for continuous integration and delivery. Optimize application performance and scalability. Review and improve code quality through peer reviews. Key Requirements Proven experience with .NET development. Strong knowledge of Docker and Kubernetes . Familiarity with Microsoft Azure and Azure DevOps Server . Experience working in Agile environments . Strong problem-solving skills. Nice to Have Experience with microservices architecture . Knowledge of additional programming languages. Familiarity with front-end technologies.

🏢 Summary: IT Project Manager role responsible for leading technical projects within defined budget, scope, and schedule while coordinating cross-functional development teams. The position focuses on Agile-driven software delivery, stakeholder communication, risk management, and ensuring high-quality project execution in multi-team environments. 🗂️ Requirements: Minimum 3 years of IT project management experience, Experience in software development environments, Customer-facing project delivery experience, Strong knowledge of Agile methodologies, Experience working with multiple development teams, Proficiency in JIRA, Ability to manage project scope, budget, and schedule, Experience in risk management and project documentation 📃 Skills: Agile, Scrum, JIRA, SDLC, UserStories, Backlog, DoD, ProjectManagement, RiskManagement, Documentation 🏢 Description: Key Responsibilities Manage technical projects to ensure adherence to budget, schedule, and scope. Develop and revise project proposals, including objectives, technologies, and staffing. Set and track project milestones while managing unforeseen delays and realigning expectations. Establish communication plans and provide status updates to stakeholders and staff. Facilitate the gathering and validation of project requirements. Maintain comprehensive project documentation and performance databases. Analyze risks and provide regular updates to Senior Management to minimize delivery delays. Coordinate internal and external resources to keep projects within defined constraints. Communicate regularly with clients to confirm schedules and resolve project issues. Requirements At least three years of management experience in the IT field, including development and customer-facing work. Strong knowledge of software development industry standards and Agile techniques (e.g., user stories, backlogs, DoD). Experience delivering projects in environments involving multiple development teams and cross-functional setups. Proficiency in project management software, specifically JIRA. Excellent communication, negotiation, and influencing skills to coordinate with vendors and management. Proven ability to create proactive, self-organizing teams with a continuous improveme