ML / AI Engineer
New
L
LingaroAI engineering
Listing location: Poland; Workplace type: Remote; You can choose to work remotely or in the office., Availability to work between 2:00 PM and 10:00 PM CET is preferred.Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- At least 5+ years of hands-on software engineering experience
- Required Skills
- AWSPythonAzureGenerative AI
Requirements
- Have at least 5+ years of hands-on software engineering experience, including significant work on production-grade AI or data-intensive systems.
- Demonstrate excellent Python programming skills.
- Have proficiency in Azure and AWS cloud platforms.
- Bring hands-on experience with Generative AI technologies and applications.
- Understand LLMs, retrieval-augmented generation, tool use, and agents, including real-world trade-offs and failure modes.
- Have experience designing and operating end-to-end AI systems across APIs, application services, data pipelines, retrieval layers, evaluation workflows, and cloud infrastructure.
- Be able to define measurable AI quality criteria and evaluation approaches.
- Have practical experience with AI-assisted engineering, Spec-Driven Development, and modern developer tooling.
- Demonstrate architectural judgment in designing reusable patterns and shared capabilities.
- Have experience contributing to cross-functional work from prototyping through production rollout and continuous improvement.
- Hold a master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or have equivalent experience.
Responsibilities
- Build and 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 technical artifacts such as specifications, evaluations, interface definitions, and workflow contracts.
- Define evaluation-driven development loops for AI system quality, reliability, latency, cost, and grounding.
- Partner with product teams to identify cross-product opportunities and support integration of shared capabilities.
- Contribute to AI-assisted development workflows, Spec-Driven Development, automated testing, and engineering agents.
- Apply standards and guardrails for AI reliability, observability, governance, security, and responsible production use.
- Prototype and validate technical approaches, developing scalable building blocks.
- Support other engineers through technical collaboration, peer review, and knowledge sharing.
- Work with AI product, engineering, and business stakeholders to align implementation choices with customer value and measurable outcomes.
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