AI Engineer

Laminar Projects

. Design and implement lean, fit-for-purpose AI/LLM solutions, balancing quality, performance and cost .

Posted 9/29/2026full-timeRemote • Portugal, PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing AI/LLM solutions, with a strong foundation in Python and ML frameworks. Capable of integrating AI capabilities into applications while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

LLMs Application ExperienceGenerative AI ImplementationPython ProficiencyMLOps FamiliarityProduction Experience with Vector Databases

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

LLMsGenerative AIPythonLangChainTransformersOpenAI APIsEmbeddingsVector DatabasesRetrieval-Augmented GenerationMulti-Model Evaluation

Soft Skills

Clear Communication

Tools & Technologies

DockerKubernetesPineconeWeaviateFAISS

Industry Keywords

AI SolutionsAI Feature LifecyclePrompt EngineeringModel SelectionFine-TuningEvaluationObservabilityScalingReliabilitySecurity

Tech Stack

Tools & technologies

DockerKubernetesPython

About the role

Key responsibilities & impact

Design and implement lean, fit-for-purpose AI/LLM solutions, balancing quality, performance and cost
Design, build and deploy AI-powered features across Shape App and Channels
Work with product teams to translate user needs into AI opportunities and technical requirements
Own the AI feature lifecycle from exploration and prototyping through production deployment and iteration
Integrate AI capabilities into applications using prompt engineering, model selection, fine-tuning and evaluation
Contribute production-grade code alongside other engineers
Collaborate with SREs on infrastructure, observability, scaling, reliability and security
Continuously explore developments in LLMs and generative AI with a product-first mindset
Act as the go-to expert on AI/LLMs and help shape the company’s AI capability

Requirements

What you’ll need

Strong experience in applying LLMs and generative AI to real-world problems
Solid foundation in Python and ML frameworks (e.g. LangChain, Transformers, OpenAI APIs)
Experience with multi-model evaluation and feedback loops
Production experience with embeddings, vector databases such as Pinecone, Weaviate or FAISS, and retrieval-augmented generation (RAG) architectures
Familiarity with MLOps tooling and observability for inference pipelines
Ability to communicate clearly with engineers, designers and non-technical stakeholders
Nice to have: familiarity with production environments, APIs, and containerised systems (Docker, Kubernetes)
Nice to have: participation in AI communities, papers or OSS projects
Applicants are encouraged to submit a letter explaining why they want to join and where they could make the most impact

Benefits

Comp & perks

Competitive salary dependent on location and capability
Paid Annual Leave (Number of days will depend on where you are based) + statutory Bank Holidays
In-House Coaching Sessions
Discretionary bonus scheme for all team members
4 Day Weeks
Flexibility in working hours and personal appointments
Coach, mentor, well-being therapist and a development-orientated environment
Fast progression and unbounded development opportunities