AI/ML Engineer

Lingaro is a company operating since 2008 with over 1800 talents in 7 global sites. It offers international projects with options to work remotely or in office locations including Warsaw, Poland.

• At least 5+ years of hands-on software engineering experience including significant work on production-grade AI or data-intensive systems.
• Excellent programming skills in Python.
• Proficiency in Azure and AWS cloud platforms.
• Hands-on experience with Generative AI technologies and applications.
• Strong understanding of LLMs, retrieval-augmented generation, tool use, agents, and their practical trade-offs and limitations.
• Experience designing and operating end-to-end AI systems including APIs, application services, data pipelines, retrieval layers, workflows, and cloud infrastructure.
• Ability to define measurable quality criteria and evaluation approaches balancing value, reliability, latency, cost, and maintainability.
• Practical knowledge of AI-assisted engineering, Spec-Driven Development, and modern developer tooling.
• Strong architectural judgment to design reusable patterns and shared capabilities.
• Demonstrated ability to contribute in agile environments from prototyping to production rollout and improvement.
• Ability to support and influence other engineers, raise technical standards, and clarify decisions in fast-changing AI environments.
• Strong communication and collaboration skills to translate technical complexity for product, engineering, and business stakeholders.
• Adaptive mindset with openness to continuous change and high learning agility.
• Master's degree in Computer Science, Software Engineering, AI, or related technical field, or equivalent experience.

• Build and continuously evolve shared AI capabilities, reusable services, and engineering accelerators for multiple construction software products.
• Design and implement production-grade AI systems including LLM-based experiences, retrieval pipelines, tool use, orchestration layers, and agentic workflows.
• Create human- and machine-executable technical artifacts such as specifications, evaluations, interface definitions, and workflow contracts.
• Define and apply evaluation-driven development loops for AI systems covering quality, reliability, latency, cost, grounding, and other performance dimensions.
• Partner with product teams to identify cross-product opportunities and support integration of shared AI capabilities.
• Contribute to AI-native engineering practices such as Spec-Driven Development, AI-assisted workflows, automated testing, and engineering agents.
• Apply standards and guardrails for AI reliability, observability, governance, security, and responsible production use.
• Prototype and validate new technical approaches to turn emerging AI capabilities into scalable building blocks.
• Support and guide other engineers through collaboration, peer review, and knowledge sharing.
• Work with AI product management and business stakeholders to align implementation with customer value and measurable outcomes.