AI/ML Engineer

Lingaro operates with over 1800 talents across 7 global sites since 2008, offering stable employment and a Great Place to Work® certified environment.

• Around 5+ years of hands-on software engineering experience, including production-grade AI or data-intensive systems in complex environments.
• Excellent Python programming skills.
• Proficiency in Azure and AWS cloud platforms.
• Hands-on experience with Generative AI technologies and applications.
• Strong practical understanding of LLMs, retrieval-augmented generation, tool use, agents, and their real-world trade-offs and failure modes.
• Experience designing and operating end-to-end AI systems across APIs, application services, data pipelines, retrieval layers, evaluation workflows, and cloud infrastructure.
• Ability to define measurable quality criteria and evaluation approaches balancing value, reliability, latency, cost, and maintainability.
• Practical experience with AI-assisted engineering and Spec-Driven Development.
• Strong architectural judgment for reusable patterns and collaboration with product teams.
• Demonstrated track record of working cross-functionally from prototyping to production in agile environments.
• Ability to support and influence engineers, raise standards, and create clarity in fast-changing AI settings.
• Strong communication and collaboration skills to translate technical complexity for stakeholders.
• Adaptive mindset with high learning agility in rapidly advancing AI fields.
• Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or related field; equivalent experience considered.

• Build and continuously evolve shared AI capabilities, reusable services, and engineering accelerators for 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 specs, evals, interface definitions, and workflow contracts.
• Define and apply evaluation-driven development loops for AI systems, covering quality, reliability, latency, cost, grounding, and performance.
• Partner with product teams to identify high-value cross-product opportunities and recommend patterns without owning product-specific architecture decisions.
• Contribute to AI-native engineering practices through Spec-Driven Development, AI-assisted workflows, automated testing, and intelligent agents.
• Apply practical standards and guardrails for AI reliability, observability, governance, security, and responsible AI production use.
• Prototype and validate new technical approaches quickly to turn emerging AI capabilities into scalable building blocks.
• Support and guide other engineers through technical collaboration, peer review, and knowledge sharing.
• Work closely with AI PM/PO, engineering, and business stakeholders to align implementation with customer value and measurable outcomes.