AI Engineer developing innovative AI-driven products for commercial real estate transactions. Collaborating with cross-functional teams to transform the way real estate professionals conduct due diligence.
Responsibilities
Take ownership of key AI technology decisions and lay the groundwork for the company’s ambitious growth plans.
Design, develop, and deploy AI-driven systems and features, integrating state-of-the-art LLMs.
Collaborate with a cross-functional team (AI Engineers, AI product managers, VP of AI, real estate legal domain experts and software engineers) to define user stories, rapidly experiment, and ship new features directly to customers to use
Explore and implement advanced concepts such as multi-agent systems, retrieval-augmented generation (RAG), agentic architectures and next generation OCR pipelines
Champion quality and reuse across the product and the codebase.
Work across the business to ensure the features you develop have a real impact on customers and move key business metrics as we design and build a brand-new product that doesn’t yet exist in the market.
Participate in architecture and code reviews to continuously improve the quality, maintainability, security, and scalability of our applications.
Requirements
You have a background in software engineering and have made the transition into AI Engineering, or are motivated to make that transition.
You are excited about the potential of LLMs, AI agents, and agentic architectures.
You have in depth experience with full stack or backend Python development.
You value shipping early and often to get customer feedback and then iterating quickly to improve the product.
You have excellent verbal and written communication skills in English.
You have proven experience delivering large, complex software engineering systems.
Prior experience with LLMs (OpenAI’s GPT-5, o1, and Claude models from Anthropic) or agentic systems.
Any Frontend experience.
Proven expertise in building highly secure, fault-tolerant APIs.
Experience building high-performance, distributed systems at scale.
A strong understanding of modern dev practices like 12 Factor, CI/CD, and observability tools such as Datadog or Prometheus.
Exposure to GraphQL APIs and WebSockets for real-time interactions.
Benefits
Competitive starting salary
Matched pension contributions
Flexible working hours and location
25 days paid holiday (plus bank holidays)
Professional equipment and personal development budget along with training opportunities to learn and develop your skills
Cycle-to-work scheme
An inclusive community enjoying all-company off-sites, lunches and socials
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