• 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

• Own the technical architecture for Buildertrend’s internal AI platform, designing reusable services, agentic systems, workflow orchestration, and AI capabilities that power teams across the GTM and G&A functions. • Establish the engineering standards for internal AI development, including architecture patterns, reusable components, evaluation frameworks, observability, governance, and deployment practices. • Architect the integration and data layer that connects Buildertrend’s business tools, including Salesforce, Gong, Databricks, and others, into a scalable internal AI platform. • Lead technical evaluations and build-vs-buy decisions for AI platforms, frameworks, and tooling in partnership with the Director of AI Enablement. • Establish best practices for monitoring, evaluating, and continuously improving AI systems in production to ensure reliability, security, and business value. • Translate ambiguous business problems from non-technical partners into well-scoped technical solutions and drive them to completion independently. • Serve as the technical voice of the Central AI Enablement function in cross-functional conversations, including engineering leadership and business VPs. • Embrace using AI as a tool to enhance your work, while remaining open to learning, applying critical thinking, and owning the quality of your final work.