AI/ML Engineer - freelancer

Lever, Inc.; Polska; On-site; PLN 200,000 - 320,000; Full time

Job summary

Lever, Inc. is seeking an experienced software engineer to help build and evolve AI capabilities across multiple construction software products.

You will design production-grade AI systems, implement retrieval pipelines and agent workflows, and create artifacts that improve clarity, speed, and quality of delivery. The role requires hands-on experience with Generative AI, LLMs, and cloud platforms, plus strong architectural judgment and collaboration across product and engineering teams.

Qualifications

• 5+ years hands-on software engineering experience in production-grade AI or data-intensive systems.
• Excellent Python programming skills.
• Proficiency in Azure/AWS cloud platforms.
• Hands-on experience with Generative AI technologies and applications.
• Strong understanding of LLMs, retrieval-augmented generation, tools, agents and trade-offs.
• Experience designing and operating end-to-end AI systems across APIs, data pipelines, retrieval layers, and cloud infra.
• Ability to define measurable quality criteria and evaluation approaches for AI systems.
• Experience with AI-assisted engineering and Spec-Driven Development.
• Strong architectural judgment to design reusable patterns and shared capabilities.
• Track record of cross-functional work from exploration to production in agile environments.
• Ability to influence engineers and raise technical standards.
• Strong communication and collaboration with product, engineering, business.
• Adaptive mindset and openness to change in fast-moving AI fields.
• Master's degree in CS/SE/AI or related field; equivalent experience considered.

Responsibilities

• Build and evolve shared AI capabilities, reusable services, and accelerators across multiple construction software products.
• Design and implement production-grade AI systems including LLM-based experiences, retrieval pipelines, tool use, orchestration layers, and agent workflows.
• Create specs, evals, interface definitions, and workflow contracts to improve clarity, speed, and quality of delivery.
• Define evaluation-driven development loops for AI systems covering quality, reliability, latency, cost, grounding, and other performance dims.
• Partner with product teams to identify high-value cross-product opportunities and support integration of shared capabilities.
• Contribute to AI-native engineering practices via Spec-Driven Development, AI-assisted workflows, automated testing, and intelligent agents.
• Apply guardrails for AI reliability, observability, governance, security, and responsible production use.
• Prototype and validate new technical approaches, turning AI capabilities into scalable building blocks with business relevance.
• Support and guide engineers through collaboration, peer review, and knowledge sharing in AI engineering.
• Work with AI PM/PO, engineering, and business stakeholders to align implementation with customer value and measurable outcomes.

Skills

Python

Azure/AWS

Generative AI

LLMs & RAG

End-to-end AI systems

Quality criteria

AI-assisted engineering

Architectural patterns

Cross-functional collaboration

Communication skills

Adaptability

Education

Master's degree in Computer Science, Software Engineering, AI, or related field

Job description

Tasks:

• Build and continuously evolve shared AI capabilities, reusable services, and engineering accelerators that can be adopted across 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 that improve clarity, speed, and quality of delivery.


• Define and apply evaluation-driven development loops for AI systems, covering quality, reliability, latency, cost, grounding, and other relevant performance dimensions.


• Partner with product teams to identify high-value cross-product opportunities, support integration of shared capabilities, and recommend patterns without owning product-specific architecture decisions.


• Contribute to AI-native engineering practices inside the team through Spec-Driven Development, AI-assisted development workflows, automated testing, and intelligent engineering agents.


• Apply practical standards and guardrails for AI reliability, observability, governance, security, and responsible production use of AI solutions delivered by the central team.


• Prototype and validate new technical approaches quickly, turning emerging AI capabilities into scalable building blocks with clear business relevance.


• Support and guide other engineers through technical collaboration, peer review, and knowledge sharing in modern AI engineering and experimentation.


• Work closely with AI PM / PO, engineering, and business stakeholders to align implementation choices with customer value, delivery feasibility, and measurable outcomes.

What We're Looking For:

• At least 5+ years of hands‑on software engineering experience, including significant work on production-grade AI or data-intensive systems in complex delivery environments.


• Excellent Python programming skills.


• Proficiency in Azure/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, limitations, 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 for AI systems, balancing customer value with reliability, latency, cost, and maintainability.


• Practical experience with AI‑assisted engineering, Spec-Driven Development, and modern developer tooling; able to improve how teams work by combining human judgment with automation and agent support.


• Strong architectural judgment with the ability to design reusable patterns and shared capabilities while collaborating effectively with product teams that own their local implementation decisions.


• Demonstrated track record of contributing to cross‑functional work from early exploration and prototyping through production rollout and continuous improvement in agile environments.


• Ability to support and influence other engineers, raise technical standards through collaboration, and create clarity in ambiguous and fast‑changing AI environments.


• Strong communication and collaboration skills, with the ability to translate technical complexity into decisions and actions for product, engineering, and business stakeholders.


• Adaptive mindset, high learning agility, and genuine openness to continuous change in a field shaped by rapid advances in AI.


• Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field; equivalent experience considered for exceptional candidates.

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.