AI/ML Engineer - Freelance (Part-time)

Lingaro is a global technology partner operating since 2008 with over 1,600 professionals across 7 global locations. The company promotes diversity, equity, and inclusion, fostering an ethical and respectful workplace.

• Minimum 5+ years of hands-on software engineering experience including production-grade AI or data-intensive systems.
• Excellent Python programming skills.
• Proficiency with Azure and/or AWS cloud platforms.
• Hands-on experience with Generative AI technologies and applications.
• Strong practical understanding of LLMs, retrieval-augmented generation, tool use, agents, including their trade-offs and limitations.
• Experience designing and operating end-to-end AI systems across APIs, services, data pipelines, and cloud infrastructure.
• Ability to define measurable quality criteria and evaluation for AI systems balancing value, reliability, latency, cost, and maintainability.
• Practical experience with AI-assisted engineering, Spec-Driven Development, and modern developer tooling.
• Strong architectural judgment and ability to design reusable patterns and shared capabilities.
• Demonstrated ability to contribute across the full AI lifecycle from prototyping to production in agile settings.
• Capability to support and influence engineers, raise technical standards, and manage ambiguity in fast-changing AI environments.
• Strong communication and collaboration skills for translating technical complexity to stakeholders.
• Adaptive mindset with high learning agility in rapidly evolving AI field.
• Master's degree in Computer Science, Software Engineering, AI, or related field; equivalent experience considered for exceptional candidates.

Core Responsibilities:

• 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 specs, evals, interface definitions, and workflow contracts.
• Define and apply evaluation-driven development loops covering quality, reliability, latency, cost, grounding, and performance.
• Partner with product teams to identify cross-product opportunities and support integration of shared capabilities.
• Contribute to AI-native engineering practices including Spec-Driven Development, AI-assisted workflows, automated testing, and intelligent agents.
• Apply standards and guardrails for AI reliability, observability, governance, security, and responsible AI usage.
• Prototype and validate new technical approaches to turn AI capabilities into scalable building blocks.
• Support and guide other engineers through technical collaboration, peer review, and knowledge sharing.
• Collaborate closely with AI PM/PO, engineering, and business stakeholders to align implementation with customer value and measurable outcomes.