AI Engineer for construction management software

Shape.Construction digitizes the construction industry. It began as a construction project management consultancy and develops construction management software products to help deliver projects more effectively.

• Design and implement fit-for-purpose AI and LLM solutions, balancing quality, performance, and cost
• Integrate AI features into applications, from exploration and prototyping through production deployment and iteration
• Prepare AI features for production with SRE teams, ensuring reliability, scalability, observability, and security
• Translate user needs into AI opportunities and technical requirements with product teams
• Own the AI feature lifecycle, including prompt engineering, model selection, fine-tuning, and evaluation
• Build production-grade code that integrates AI capabilities into applications alongside other engineers
• Define infrastructure, observability, and scaling requirements for AI features with SREs
• Explore developments in LLMs and generative AI and apply them with a product-first mindset

• Strong experience applying LLMs and generative AI to real-world problems
• Solid foundation in Python and ML frameworks such as LangChain, Transformers, and OpenAI APIs
• Experience with multi-model evaluation and feedback loops
• Production experience with embeddings, vector databases such as Pinecone, Weaviate, or FAISS, and RAG architectures
• Familiarity with MLOps tooling and observability for inference pipelines
• Bias for simplicity, clarity, and iterative delivery
• Ability to communicate clearly with engineers, designers, and non-technical stakeholders
• Shape may not be a fit for candidates who want an easy role without much challenge, want to be the smartest person in the room, dislike receiving honest feedback, or prefer working independently rather than with a team
• Будет плюсом: familiarity with production environments, APIs, and containerized systems such as Docker and Kubernetes; participation in AI communities, papers, or OSS projects

• Competitive salary dependent on location and capability
• Paid annual leave; the number of days depends on location, plus statutory bank holidays
• In-house coaching sessions
• Discretionary bonus scheme for all team members
• Four-day work weeks
• Flexible schedule focused on getting things done; no permission is needed for personal commitments such as picking up children or going to the doctor, but the team should be kept informed if affected
• Coaching, mentoring, well-being therapy, and a development-oriented environment
• Fast progression in a meritocratic environment, with support to develop in areas of interest
• The role offers a four-day work week