• Build our agentic SDLC pipeline. Design, implement, and operate agentic workflows across the development lifecycle - planning, code generation, review, testing, documentation, and release that is all integrated with our GitOps and CI/CD infrastructure. • Level up developer experience. Bring modern AI integrations into the daily workflow of our engineering team: coding agents, automated review, intelligent test generation, and self-service tooling that removes friction and multiplies output. • Engineer grounded, trustworthy systems. Build retrieval-grounded and context-aware AI systems that produce reliable, verifiable results and design the evaluation harnesses that prove it. • Establish governance and guardrails. Define and implement the policies, human-in-the-loop checkpoints, audit trails, and security controls that let us adopt agentic AI responsibly in environments where trust is non-negotiable. • Formalize and scale. Turn what works into repeatable frameworks, playbooks, and internal platforms that extend agentic acceleration beyond engineering to the whole organization. • Champion the practice. Evangelize, teach, and support AI adoption across the team; you'll be a force multiplier, not a silo.

• Lead AI System Design & Development • Develop real-time and batch inference pipelines integrated with streaming data platforms. • Design feature engineering pipelines leveraging high-volume behavioral and content metadata. • Implement end-to-end ML workflows from data ingestion to model serving. • Build AI-Powered Data Products • Develop production-grade AI services that power user-facing and internal data products. • Design APIs and services to expose AI capabilities to downstream applications and platforms. • Ensure tight integration between AI systems and the core data platform. • Architect Scalable ML Infrastructure • Define architecture for model training, evaluation, deployment, and monitoring. • Build and optimize feature stores, model registries, and inference services. • Design systems that support low-latency, high-throughput model serving. • Establish best practices for reproducibility, versioning, and lifecycle management. • Production Reliability & Model Performance • Monitor and optimize model performance, latency, and system reliability in production. • Implement observability for data quality, feature drift, and model degradation. • Establish automated testing, validation, and deployment pipelines for ML systems. • Ensure scalability and cost efficiency across AI workloads. • Cross-Functional Collaboration • Partner with Data Engineers to integrate AI pipelines with real-time and batch data systems. • Collaborate with Product Managers to define AI-driven product capabilities and roadmap. • Work with Software Engineers to integrate AI services into user-facing applications. • Align with analytics and experimentation teams to measure model impact. • Technical Leadership • Lead architectural decisions for AI/ML systems and data-driven applications. • Mentor engineers in machine learning engineering, system design, and best practices. • Establish standards for model development, deployment, and operational excellence. • Drive innovation in applied AI across streaming and content platforms.

Role Description In this role, you will: - Build and deploy production-ready LLM applications on cloud infrastructure - Design AI agents capable of reasoning through complex problems - Integrate AI solutions with existing systems, including ERPs, CRMs, and data warehouses - Implement monitoring and performance optimization solutions to identify potential issues before they impact users - Own the end-to-end machine learning pipeline, from prototyping to production deployment - Lead the development team and contribute to key technical decisions - Collaborate directly with stakeholders to understand business needs and translate them into effective AI solutions Qualifications - Strong Python programming skills and experience writing production-level code - Hands-on experience with LLM frameworks and technologies such as RAG, MCP, LangChain, or LlamaIndex - Solid knowledge of SQL and NoSQL databases - Familiarity with CI/CD principles and pipelines - Practical experience with AWS cloud services - Curiosity about emerging technologies and motivation to build innovative products from scratch - Ability to adapt and stay effective in a fast-changing environment - Experience leading or supporting a development team - Clear communication skills and the ability to collaborate directly with stakeholders - Fluency in both Lithuanian and English, written and spoken Benefits - A working culture that is high performing, ambitious, collaborative, and fun - Private medical care - Sports package - Life insurance - Flexible working hours - Employee-led workshops and office perks - B2B contracts include paid annual service break and paid public days-off in Poland - Salary range: 127 - 190 PLN/h + VAT (B2B) or 17 650 - 26 500 PLN gross (Permanent)

• Collaborate with cross-functional teams to deliver high-quality AI-driven applications • Design scalable systems and justify technical decisions • Implement event-driven architecture and asynchronous workflows • Mentor team members on AI engineering best practices • Drive technical leadership initiatives within the team