[All remote jobs](https://jobicy.com/jobs.md)[![Laminar Projects logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/5bd8df6b-221.png)](https://jobicy.com/company/laminar-projects.md)[Laminar Projects](https://jobicy.com/company/laminar-projects.md) # AI Engineer – 4 Day Week + Remote Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/laminar-projects.md)ShareRemote from[Portugal](https://jobicy.com/job-region/portugal.md), [Poland](https://jobicy.com/job-region/poland.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceOpen levelPublished17 Oct 2026Apply before16 Nov 2026Listing views35Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. This AI Engineer will develop and productionize LLM-powered capabilities for construction-management products. The role spans opportunity discovery, prototyping, prompt and model design, evaluation, and integration of AI features into applications. It requires strong Python and generative-AI engineering skills, including RAG, embeddings, vector databases, inference observability, and collaboration with SRE teams. The position is full-time, remote for candidates located in Portugal or Poland, and emphasizes pragmatic delivery, feedback, and a four-day workweek. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior-level applied AI engineering role requiring both hands-on LLM expertise and the ability to make sound production, cost, reliability, and product trade-off decisions. The engineer is expected to own the AI feature lifecycle while coordinating closely with product, engineering, and SRE stakeholders. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$150,000US market range (per year)$120k–$180k0$198.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer pay amount is disclosed. The job period is inferred as yearly because this is a full-time professional engineering role. Estimated annual market compensation is shown in USD for comparison only; actual compensation is stated to depend on candidate location and capability. ## Core skills Skills and capabilities most closely associated with this opportunity. [Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[Generative AI](https://jobicy.com/jobs?search_keywords=Generative%20AI.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Prompt Engineering](https://jobicy.com/jobs?search_keywords=Prompt%20Engineering.md)[Retrieval-Augmented Generation](https://jobicy.com/jobs?search_keywords=Retrieval-Augmented%20Generation.md)[Embeddings](https://jobicy.com/jobs?search_keywords=Embeddings.md)[Vector Databases](https://jobicy.com/jobs?search_keywords=Vector%20Databases.md)[Pinecone](https://jobicy.com/jobs?search_keywords=Pinecone.md)[LangChain](https://jobicy.com/jobs?search_keywords=LangChain.md)[OpenAI API](https://jobicy.com/jobs?search_keywords=OpenAI%20API.md)[Model Evaluation](https://jobicy.com/jobs?search_keywords=Model%20Evaluation.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[Inference Observability](https://jobicy.com/jobs?search_keywords=Inference%20Observability.md)[Docker](https://jobicy.com/jobs?search_keywords=Docker.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md) Sample interview questionsHow would you decide whether an AI feature should use a simple prompt workflow, RAG, fine-tuning, or a non-LLM solution?I would begin with the user decision or workflow being improved, the quality threshold, data availability, latency, and cost constraints. I would baseline the simplest viable approach first, introduce RAG when grounded access to changing proprietary information is needed, and consider fine-tuning only when repeatable gains justify its operational cost. I would also validate whether deterministic rules or conventional software solve the problem more reliably. Describe how you would evaluate a RAG feature before releasing it to construction users. I would create a representative evaluation set from real user tasks and documents, including difficult, ambiguous, and safety-sensitive cases. I would measure retrieval relevance, answer faithfulness, completeness, citation quality, latency, and cost, then combine automated scoring with structured human review. After launch, I would monitor production feedback, failure patterns, and drift to iteratively improve both retrieval and response behavior. What production controls would you put in place for an LLM-powered feature? I would implement structured logging, traces across retrieval and inference stages, latency and token-cost metrics, quality signals, rate limits, and clear alerting thresholds. I would ensure sensitive data handling, access controls, prompt-injection mitigations, fallback paths, and versioning for prompts, models, and evaluation datasets. I would work with SREs to define reliability objectives and safe rollout mechanisms such as feature flags and staged releases. How would you collaborate with product managers when the AI solution is uncertain? I would translate the product goal into testable hypotheses, identify the smallest experiment that can reduce uncertainty, and make trade-offs explicit in terms of user value, quality, speed, and cost. I would share examples of expected and unacceptable model behavior rather than discussing model capability abstractly. This keeps product decisions grounded in observable outcomes and supports fast iteration. Tell us about a time you had to simplify a technically ambitious AI proposal. I would explain the original objective, the risks created by complexity, and the evidence that supported a narrower first release. For example, I might replace an autonomous multi-agent workflow with a retrieval-backed assistant that has clear human review and measurable outcomes. I would show how the simplified release delivered user value sooner while creating a foundation for later expansion. Opportunity details ## About this role. Ever wondered how it would be to revolutionise one of the least digitised industries in the market, alongside a growing and switched-on team? Read on! ___________________________________________________________________________________ We are [Shape.Construction](http://shape.construction/)! We are digitising the largest and most fundamental industry in the world, the industry that literally builds the foundations of the civilisation we all depend on to spare us from a brutal hunter-gatherer life: CONSTRUCTION It is one of the least digitised industries in the world but also the largest – 1 in 9 people globally work in the construction industry and it constitutes 11% of global GDP. Improving construction strengthens the very foundation of human civilisation. ([Watch our short film about](https://youtu.be/PxcBZupiI7Y) it). We got our start as a high-end construction project management consultancy. As a consultancy, we are focused on genuinely upgrading the way construction projects are delivered. We then take the deep understanding of the projects we work on to develop construction management software products that anyone can use to deliver their projects better. We are building a full suite of products one module at a time – kind of like office 365 but for construction management. ([Check out Shape, our construction management tech](https://www.shape.construction/) and [watch this video about what we are doing](https://youtu.be/tgi4hW3G_NY)) The core of all this is our true secret sauce; people. We only recruit the very best both in capability and personality. We are deeply focused on designing a new type of organisation that is optimised for the flourishing of the people in the team first and foremost. People that join us develop fast as a whole person in ways they never imagined. ([Read more about our vision and mission](https://www.shape.construction/join-us/)). This approach has allowed us to grow from just 2 people in 2017 to over 200 today (including consultancy) and we are still very much at the beginning! Joining us isn’t just some “job”, it is a transformative educational experience. We challenge you to be your best self in all aspects of life. Our vision is designed to align how we operate with the fundamental aspects that enable anyone to have a fulfilled life: – Connects us with meaningful relationships – Inspires us to develop ourselves to become better humans – Empowers us to pursue our own learning adventures 4 core values for a good life We believe a life of human flourishing is all about meaningful relationships with others and challenging yourself to create a positive impact. Our four core values are grow yourself, care about people, execute to greatness and build civilisation. This philosophy goes much deeper and you can see more on our website. We are achieving this vision through the following two missions:  1. To fully digitise the construction of human civilisation 2. To create a new type of organisation that enables human flourishing while delivering a huge positive impact on society Laminar Projects is proud to be recognized as one of the UK’s Best Workplaces in Construction, Engineering & Property™ for 2024! Join a team where learning, collaboration, and growth are at the core of everything we do, and where solving big challenges is part of the fun. ___________________________________________________________________________________ The Role Purpose of the role We are looking for an AI Engineer who combines deep knowledge of Large Language Models (LLMs) with strong software engineering skills and a pragmatic approach to product development. This person will help us design, build and deploy AI-powered features across Shape App and Channels, working closely with the Product and SRE Teams to define optimal solutions and ensure they run reliably in production. You should be excited by the challenge of turning AI potential into real, useful features, for construction teams, and you should know when a small, lean approach is better than a large, complex one. Team You will join a team of product-minded software engineers, designers, and strategists focused on improving the way construction projects are delivered. You will work closely with Product Managers to shape AI features, and with our SRE Team to ensure production-readiness. You will be the go-to expert on AI/LLMs and play a key role in shaping our AI capability. Your top 3 objectives 1. Design Lean, Fit-for-Purpose AI Solutions: Choose and implement the most appropriate AI/LLM approach for each use case, balancing quality, performance and cost. 2. Integrate AI-features into our Applications: From exploration and prototyping to production deployment and iteration, using prompt engineering, model selection, fine-tuning, and evaluation. 3. Prepare for Production: Work with SREs to ensure AI features are reliable, scalable, observable, and secure in production. Your top 5 responsibilities 1. Understand the Product Context: Work with product teams to translate user needs into clear AI opportunities and technical requirements. 2. Own the AI Feature Lifecycle: From exploration and prototyping to production deployment and iteration, using prompt engineering, model selection, fine-tuning and evaluation. 3. Build AI-Backed Features: Contribute production-grade code that integrates AI capabilities into our apps, working alongside other engineers. 4. Guide Production Set-Up: Collaborate with SREs to define what infrastructure, observability, and scaling is required for each AI feature. 5. Stay Pragmatic and Up-to-Date: Continuously explore new development in LLMs and generative AI but always apply them with a product-first mindset. Your Capabilities You are a software engineer who understands how to use LLMs effectively, not just how to train them. You work well with ambiguity and know how to test your ideas quickly. You’re comfortable collaborating with product teams and setting up production-grade systems. As a candidate, you should have: – Strong experience in applying LLMs and generative AI to real-world problems. – Solid foundation in Phyton and ML frameworks (e.g. LangChain, Transformers, OpenAI APIs, etc.). – Experience with multi-model evaluation and feedback loops. – Production experience with embeddings, vector dabatases (like Pinecone, Weaviate or FAISS), and retrieval-augmented generation (RAG) architectures. – Familiarity with MLOps tooling and observability for inference pipelines. – A bias for simplicity, clarity, and iterative delivery. – The ability to communicate clearly with engineers, designers and non-technical stakeholders. Nice to Have (If you don’t have it now you will after joining) – Familiarity with production environments, APIs, and containerised systems (Docker, Kubernetes). – Participation in AI communities, papers or OSS projects. Shape isn’t the place for you if any of the following is true: – You want an easy, chilled-out role without much challenge – You like to be the smartest person in the room – You don’t like continuously receiving honest candid feedback – You prefer to do your own thing rather than work with a team At Shape we value diverse experiences and perspectives, empowering each member to contribute their unique expertise towards our collective success, so if you don’t think you meet all the criteria but still are excited about this role we encourage you to apply anyways! ___________________________________________________________________________________ Salary and Benefits Standard Stuff – 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. The Life-Changing Stuff – 4 Day Weeks: That’s right, 4 day weeks – Flexibility: Getting things done is what really matters, not what time of day you do it. That means you don’t have to ask permission for things like picking up your kids or going to the doctor, just keep your team in the loop if you think they will be affected. – Grow your whole self: Our leaders are more like coaches and one of our main objectives is to give 5 years’ worth of learning and development for every 1 year with us. You have a coach, mentor, well-being therapist and a development-orientated environment: That’s literally what our vision is all about and the primary reason Shape exists – Be surrounded by the best: We only hire and retain the very best people. You might be used to being the smartest in the room but that won’t be the case in Shape. You will be surrounded by people you can learn from. We are 100% meritocratic so fast progression is the norm. You will be supported to excel in whichever areas you are most interested in! With Shape, development is unbounded – Long-term impact: We are focused on solving the biggest issues in construction project delivery in a way that can spread and outlast us ________________________________________________________________________________________ Application We get thousands of applications so please write us a letter as part of your application explaining: – Why do you want to join us? – If you joined, where do you think you could make the most impact and how? We aren’t a giant faceless corporation; we really care about the people who want to join our team so all applications will be read thoroughly by our key leaders. In terms of application, we usually start with an intro call to tell you what we are all about in a casual conversation. That helps you to know us a bit better and tell us a bit about yourself. ### Compensation ### Additional Information Show more [Apply now >](https://jobicy.com/jobs/155579-ai-engineer-4-day-week-remote.md) > Annual salary information is not provided for this position. 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