Software Engineer (Agent Development)

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience across frontend and backend systems, System design, distributed applications and API architecture knowledge, Experience with LLMs, RAG systems or AI-powered applications, Ability to own features from concept through production deployment, Pragmatic decision-making in ambiguous, fast-moving environments, Cross-functional collaboration with engineering, Machine Learning and product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, external-tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience, Frontend and backend systems experience, System design expertise, Distributed applications knowledge, API architecture knowledge, LLM, RAG or AI-powered application experience, Production deployment ownership, Cross-functional collaboration with Engineering, Machine Learning and Product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Backend Engineer role focused on building and operating the AI inference and orchestration systems behind a production AI assistant. The position emphasizes low-latency, high-throughput APIs, distributed-system reliability, observability and performance optimization for mobile, desktop and machine-learning integrations. Remote-first collaboration is available for a candidate working from Poland, with base salary and equity assessed individually. 🗂️ Requirements: Production backend engineering experience, High-throughput, low-latency service experience, AI inference familiarity: LLMs, embeddings, multimodal models, Distributed-systems debugging under load, Production observability and incident-management knowledge, Performance-optimization expertise, Independent delivery in ambiguous environments, Working from Poland, Working-hours overlap with immediate team 📃 Skills: Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, Embeddings, SQL, NoSQL, Kubernetes, Docker, APIs, Caching, Batching, Streaming, Logging, Alerting 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role As a Backend Engineer specializing in AI systems, you will own the inference and orchestration layer behind the product’s AI interactions. Your work will sit between models and end users, where latency, correctness, reliability and operating costs directly affect the product experience. You will build and operate production systems that transform model capabilities into fast, stable and observable APIs used by mobile and desktop applications. What you will do Build and operate backend systems serving AI-powered functionality in production. Design inference pipelines, orchestration layers and service boundaries around Machine Learning models. Take ownership of production monitoring, logging, alerting and incident response. Optimize latency and throughput across inference, caching, batching and streaming. Build reliable APIs supporting integration with mobile, frontend and Machine Learning systems. Diagnose distributed-system issues under production load. Continuously improve system performance and reliability using real-world production signals. What we are looking for Strong backend engineering fundamentals supported by experience with production systems. Experience building or operating high-throughput, low-latency services. Familiarity with AI inference patterns, including LLMs, embeddings and multimodal models. Confidence debugging distributed systems under load. Understanding of production observability, incident management and performance optimization. A delivery-oriented mindset focused on shipping, observing production behavior and improving through iteration. Ability to work independently and make pragmatic engineering decisions in an ambiguous environment. What success looks like Backend systems reliably handle production AI traffic at scale with low latency and high throughput. APIs remain stable, clear and easy to integrate with frontend, mobile and Machine Learning systems. Production incidents are detected quickly, diagnosed effectively and resolved with minimal impact on users. System performance and reliability improve continuously based on real-world usage and production data. Technology stack Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with backend, Machine Learning, mobile and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Lead an international multidisciplinary engineering team delivering and modernizing recruitment technology, including business-critical document-parsing systems and AI-driven solutions. The hybrid role combines people management, delivery ownership, and technical leadership across global product and engineering stakeholders. 🗂️ Requirements: 2+ years leading software engineers as an Engineering Manager, Software Development Manager, Technical Lead, or similar, Experience leading agile product engineering teams, Experience managing delivery, capacity, risks, and technical priorities, Experience mentoring engineers, managing performance, and supporting career growth, Previous hands-on software engineering experience, Strong knowledge of software architecture, APIs, CI/CD, cloud environments, and modern development practices, Understanding of machine learning and LLM-based product applications, Ability to assess architecture, technical debt, quality, scalability, and engineering trade-offs, Experience working in distributed international organizations, Practical experience using AI tools in engineering or management workflows, Fluent English 📃 Skills: Python, Perl, APIs, CI/CD, AWS, MachineLearning, DeepLearning, LLMs, GitHubCopilot, Claude, Gemini, ChatGPT 🏢 Description: We are hiring on behalf of our client, a global leader in HR technology, delivering an end-to-end SaaS platform that supports the entire recruitment lifecycle. Trusted by thousands of organizations worldwide, their solutions combine cloud technology, automation, and cutting-edge AI to help businesses hire smarter, work more efficiently, and deliver better talent experiences. We are looking for a Lead/Manager to lead an international team of Software Engineers, AI Engineers, and Data Analysts. This is primarily a people leadership and delivery role with a strong technical component . You will coach the team, drive predictable execution, partner with Product and Engineering leaders across Europe and North America, and help modernize a technology stack that combines legacy systems with AI-driven solutions. Key takeaways: Stack: Python, Machine Learning, Deep Learning, LLMs, APIs, CI/CD, AWS, leadership experience Salary: 23 000 PLN - 28 500 PLN gross on the Contract of Employment Working model: hybrid - 3x weekly from the office Location: Krakow Recruitment process: A call with Motife recruiter (30 min) Criteria Cognitive Aptitude Test (30 min) Hiring Manager Interview (30 min) Technical Interview (90 min) Responsibilities: Team Leadership Lead and support a multidisciplinary engineering team of up to 11 Software Engineers, AI Engineers, and Data Analysts. Coach team members through regular 1:1s, structured feedback, performance reviews, and individual development plans. Build a high-trust environment based on transparency, ownership, constructive feedback, and continuous development. Delivery & Engineering Excellence Own sprint execution, workload planning, delivery predictability, and proactive risk management. Partner with engineers and architects to maintain software quality, address technical debt, and improve engineering processes. Ensure the team balances new development with the stability and maintainability of business-critical parsing systems. Product & Global Collaboration Partner with Product Managers and Product Owners to refine priorities, assess technical complexity, and translate business needs into achievable engineering plans. Coordinate with engineering leaders and stakeholders across Europe and North America. Ensure engineering initiatives contribute directly to customer value and wider business objectives. AI & Technology Modernization Guide the evolution of document-processing technologies combining Perl, Python, machine learning, deep learning, and LLM-based approaches. Drive practical adoption of AI tools across engineering, testing, development, and team workflows. Identify opportunities to modernize legacy solutions without compromising reliability or operational performance. Requirements: Leadership Experience 2+ years of experience as an Engineering Manager, Software Development Manager, Technical Lead, or similar role with direct responsibility for software engineers. Proven experience leading agile product engineering teams and managing delivery, capacity, risks, and technical priorities. Strong track record of mentoring engineers, managing performance, and supporting career progression. Technical Expertise Previous hands-on software engineering experience and the technical depth required to effectively manage experienced engineers. Strong understanding of software architecture, APIs, CI/CD, cloud environments, and modern software development practices. Good understanding of machine learning and LLM-based technologies and how they can be applied within software products. Ability to discuss architecture, technical debt, software quality, scalability, and engineering trade-offs with senior technical stakeholders. Collaboration & Mindset Experience working in distributed, international organizations, ideally across European and North American time zones. Strong ownership mindset with the ability to communicate risks clearly and make pragmatic decisions. Practical experience using AI tools such as GitHub Copilot, Claude, Gemini, or ChatGPT within engineering or management workflows. Fluent English and strong written and verbal communication skills. What we offer: Medical care Life insurance Multisport Apply now If you combine strong people leadership with solid engineering judgment and an interest in practical AI adoption, we’d like to hear from you! Apply via our careers page and please submit your CV in English.

🏢 Summary: Lead AI Software Developer role focused on architecting and scaling AI-powered applications, backend services, and enterprise integrations. The position leads AI agent and LLM solution development, technical standards, mentoring, and cloud-based automation delivery. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, or similar field, 8+ years of software engineering experience, 5+ years of production Python backend development, Experience building and scaling Python applications, Hands-on experience with AI Agents, RAG, and MCP, Experience with AWS or Azure, storage, databases, and AI services, Knowledge of containerization and Kubernetes, Experience with API integrations and enterprise system connectivity, Leadership and mentoring experience, Fluent Polish and English at B2 minimum, Willingness to travel internationally up to 10% 📃 Skills: Python, AWS, Azure, RAG, MCP, Kubernetes, APIs, Databases, Containers, LLMs 🏢 Description: We are seeking an experienced Lead AI Software Developer to design and scale AI-powered applications and integrations. In this role, you will architect backend systems, lead AI agent development, and ensure secure, scalable integration across cloud platforms and enterprise systems. Key Responsibilities Design and maintain middleware, APIs, and connectors integrating AI agents with enterprise systems Architect scalable backend services and cloud-based solutions (AWS/Azure) Develop and optimize multi-agent workflows and adaptive decision logic Fine-tune prompts and LLM-based solutions for domain-specific use cases Lead code reviews, mentor developers, and define development best practices Drive complex API integrations with internal and external AI platforms (incl. MCP servers) Remove technical roadblocks and ensure timely delivery Collaborate with AI, Data, and Platform teams to optimize automation architectures Maintain technical documentation and promote continuous improvement Requirements Degree in Computer Science, AI, Data Science, or similar field 8+ years of software engineering experience, including 5+ years of Python backend development (production) Strong experience building and scaling Python applications Hands-on experience with AI technologies (AI Agents, RAG, MCP) Experience with cloud platforms (AWS or Azure), storage, databases, and AI services Knowledge of containerization and Kubernetes Experience with API integrations and enterprise system connectivity Strong leadership and mentoring experience Excellent communication skills; fluent in Polish and English (min. B2); German is a plus Willingness to travel internationally (~10%) Nice to have: Experience with LangChain, LangGraph, multi-agent systems, prompt engineering, and LLM fine-tuning. What We Offer Work in a global and innovative technology environment Direct impact on enterprise AI and automation solutions Professional development and access to training programs Hybrid work model with flexible hours (central Wroclaw office) Competitive benefits package, cafeteria system, CSR initiatives, and employee clubs

🏢 Summary: Backend Engineer role focused on building AI-centric digital products for employees and HR stakeholders. The position involves Java/Spring Boot microservices development, API and cloud integration, production observability, and maintaining secure, reliable solutions in a hybrid Kraków or Wrocław work model. 🗂️ Requirements: Strong Java and Spring Boot experience, Spring Batch and Spring Cloud experience, Microservices development experience, REST API and GraphQL schema design proficiency, NoSQL data modelling experience, Data streaming experience, OAuth 2.0 and Microsoft Entra ID knowledge, Azure Cloud Services familiarity, English communication skills, Agile collaboration experience, Commitment to quality, maintainability and documentation 📃 Skills: Java, SpringBoot, SpringBatch, SpringCloud, Microservices, REST, GraphQL, NoSQL, CosmosDB, Kafka, OAuth2, EntraID, Azure, AppServices, AzureMonitor, APIManagement, Observability, Testing 🏢 Description: Role summary We are looking for a Backend Engineer to design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. 📍 Work mode: Hybrid (2–3 days/week) — Kraków or Wrocław office Primary skills Java, Spring Boot, microservices, REST APIs Key responsibilities: Design, develop, and continuously improve intelligent digital products and services that support employees and HR stakeholders, with AI at the core. Apply modern engineering practices, from analyzing user needs and developing new features to automated testing, deployment, and observability. Ensure quality, security, reliability, and compliance by applying digital principles and implementing functional and non-functional requirements. Build observability into solutions, monitor production health, help resolve incidents, and remediate root causes of risks and issues. Advocate for user and stakeholder needs, ensuring AI solutions are explainable, ethical, and human-centric. Share knowledge openly, contribute to hiring and onboarding, and help shape a collaborative, forward-thinking engineering culture. Required skills and experience: Strong experience in Java and Spring Boot, including Spring Batch and Spring Cloud, and building microservices. Proficiency in REST API and GraphQL schema design. Experience with NoSQL data modelling, such as Azure Cosmos DB ; data streaming, such as Confluent Kafka; and authentication/authorization protocols, including OAuth 2.0 and Microsoft Entra ID. Familiarity with Azure Cloud Services , including App Services, Azure Monitor, and API Management. Collaborative communication skills: able to express ideas clearly in English and adapt technical content for diverse audiences while working closely with product managers, designers, and engineers in agile settings. Strong commitment to quality, maintainability, documentation, and continuous learning. AI-related skills, such as Spring AI or LangChain, are a strong plus. Benefits ✅ Stable long-term cooperation with opportunity for extension Opportunity to work with modern technologies in an international environment Professional growth and continuous development opportunities Participation in challenging and impactful projects 📩 If you’re interested and meet the qualifications, please send your CV at alina.pchelnikova@dcvtechnologies.co.uk