At a Glance
- Tasks: Design and build innovative AI systems for real-world design challenges.
- Company: Join Woods Bagot, a global leader in architecture and design.
- Benefits: Flexible work locations, inclusive culture, and opportunities for growth.
- Other info: Collaborative team atmosphere with a focus on learning and development.
- Why this job: Be at the forefront of AI innovation in a creative environment.
- Qualifications: 3-5 years in AI/ML or complex systems; Python proficiency required.
The predicted salary is between 60000 - 80000 £ per year.
We are flexible regarding which Woods Bagot studio you are based in, options including Sydney, Melbourne, Brisbane, Adelaide, Perth, San Francisco, Los Angeles.
About Woods Bagot – Architecture for Worlds Ahead. We design places that meet the challenges and opportunities of our rapidly changing world. Our commitment to exploration, impact and community creates enduring, forward‑thinking outcomes, unlocking humanity’s highest potential. With a global design culture devoted to creativity, resilience, and purpose – we ensure every project contributes to our client’s vision, inspiring future generations.
Woods Bagot is part of the 7C Network. The 7C Network is an integrated network of design and architecture companies that provides “Total Place Design,” a holistic approach to creating transformative environments. It combines capabilities from its constituent brands – including Woods Bagot, ERA‑co, Impact Futures, and Customs Bureau – to offer services in placemaking, sustainability, architecture and interior design, and luxury concepts.
About the Role. You will join an established Design Technology team within the 7C Network, working across and supporting all the 7C brands, including Woods Bagot. The role sits within a focused AI innovation group operating at the intersection of design practice and emerging technology, building tools and systems that make institutional knowledge more accessible and automate existing work processes, across both design and non‑design functions. As an AI Specialist, you will design, build, and operate production‑ready AI systems – including multi‑agent workflows and retrieval‑augmented generation (RAG) – that can reason, retrieve, and recommend across complex design and operational problems. You will work closely with a Full Stack Engineer, subject matter experts, designers, and project leadership to deliver solutions that are usable, trustworthy, and impactful in real project environments.
This role is intentionally open to strong candidates from either:
- AI‑experienced backgrounds outside AEC (who can learn the domain quickly with support from SMEs),
- AEC technology/computational backgrounds (who can rapidly deepen AI/LLM system skills as part of the role).
The role spans the full lifecycle: from early prototype through to deployment and ongoing operation, in a fast‑moving environment that values clear thinking, technical depth, and independent decision‑making.
Key Areas of Responsibility:
- Design, build, and deploy production‑ready AI systems, including multi‑agent workflows, for real‑world design and operational use cases.
- Develop and maintain RAG pipelines, including chunking strategies, retrieval methods, reranking, hybrid search, and evaluation.
- Translate ambiguous practice problems into clear, testable system behaviours (e.g., reasoning steps, retrieval logic, and measurable output quality).
- Fine‑tune and/or configure language models and prompts for domain‑specific tasks, using real‑world feedback loops to improve performance and reliability.
- Build and operate data ingestion pipelines, including live feeds from external APIs and web sources where appropriate.
- Integrate agents, models, data sources, and interfaces into cohesive workflows that are reliable, understandable, and usable by project teams.
- Collaborate across design, product, and engineering to ensure solutions align to user needs, constraints, and delivery realities.
- Own delivery from prototype to deployment, including refinement, release, and ongoing operational maintenance.
About You. You are comfortable working within a small, high-trust team environment where you are empowered to make decisions, move quickly, and clearly communicate trade‑offs. You enjoy translating complex domain problems into practical, computable workflows and are confident acting as a bridge between domain experts and technical implementation teams.
You take a pragmatic approach to your work, focusing on outcomes, reliability, and genuine user adoption rather than experimentation for its own sake. You are also able to communicate effectively with both technical and non‑technical audiences, including designers and project leadership teams.
You are fluent in AI‑assisted development workflows and are confident evaluating and adopting new tools and techniques thoughtfully and responsibly as the landscape continues to evolve. Above all, you are motivated by learning and growth. Depending on your background, you will be expected – and supported – to quickly build fluency in either AEC practice contexts or advanced AI/LLM system design.
Required Experience and Skills
General:
- 3–5 years’ experience with clear evidence of delivering production systems that real users rely on – demonstrated through either: AI/ML or LLM‑based systems, or complex computational/automation platforms with operational constraints, measurable performance, and ongoing maintenance.
- Strong proficiency in Python and modern software development practices.
- Confidence making and defending system design decisions independently, with clear reasoning and communication.
- Strong collaboration and communication skills across AI, design, product, and project leadership.
AI systems, agents, and orchestration:
- Hands‑on experience building and deploying multi‑step AI workflows (including multi‑agent systems or equivalent stateful orchestration patterns).
- Comfortable working with modern model APIs and integrating model capabilities into usable product workflows.
- Experience with prompt engineering and evaluation; fine‑tuning experience is beneficial where appropriate.
Systems integration experience: connecting models/agents with data sources, services, and user interfaces into a unified workflow.
RAG and retrieval:
- Experience designing and evaluating RAG pipelines, including chunking, retrieval strategies, reranking, and hybrid search.
- Vector database experience and familiarity with embedding pipelines.
- Understanding of retrieval strengths and failure modes, and ability to improve groundedness and relevance through evaluation and iteration.
Data and Infrastructure:
- Experience building and operating data ingestion pipelines, including from external APIs and/or web sources where appropriate.
- Experience supporting production deployment and ongoing maintenance (e.g., reliability, performance, and iterative improvement).
- Prior experience in architecture/urban design/AEC practice, including spatial planning workflows and/or working with 3D design platforms (e.g., BIM/CAD/GIS ecosystems), and/or experience deploying AI platforms in other complex, knowledge‑intensive domains (e.g., enterprise SaaS, legal, finance, healthcare, regulated or risk‑sensitive environments).
How to Apply. Please submit your up‑to‑date resume via our LinkedIn Job Post: Applications will be treated in the strictest confidence. We do not accept unsolicited resumes or names from agencies. Mandatory requirement: It is an essential requirement that at the time of applying for this position applicants must have the legal right to work in their preferred location/s (i.e. Sydney, Melbourne, Adelaide, Brisbane, Perth, San Francisco, Los Angeles).
7C – Total Place Design Network. 7C is an equal opportunity employer. We are committed to equal employment opportunity regardless of race, colour, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status. At 7C, we are committed to creating an environment where difference is celebrated, valued and respected, practices are equitable, and our people feel like they belong. We accept that none of us is smarter than all of us. We believe building a diverse workforce is the foundation to creativity and innovative design – it is only by working together that we can realise the potential of our people, clients and communities around us. Through our inclusive leadership and our truly global studio network, you will find your voice and have the support and flexibility required to bring your whole self to work and build an exceptional career.
AI Specialist in London employer: Woods Bagot
Woods Bagot is an exceptional employer that fosters a dynamic and inclusive work culture, empowering employees to innovate at the intersection of design and technology. With flexible studio locations across major cities like Sydney, Melbourne, and San Francisco, we offer unique opportunities for professional growth and collaboration within a global network dedicated to transformative design. Our commitment to diversity and community ensures that every team member feels valued and supported, making it a truly rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land AI Specialist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Woods Bagot or within the 7C Network. Attend events, webinars, or even casual meet-ups to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your AI expertise and how it can be applied in design contexts. This will give you something tangible to discuss during interviews and showcase your problem-solving abilities.
✨Tip Number 3
Prepare for interviews by understanding the company’s projects and values. Research Woods Bagot's recent work and think about how your skills can contribute to their mission of creating transformative environments.
✨Tip Number 4
Don’t just apply anywhere; apply through our website! It shows you're genuinely interested in being part of the team. Tailor your application to reflect how you align with the role and the company culture.
We think you need these skills to ace AI Specialist in London
Some tips for your application 🫡
Tailor Your Resume:Make sure your resume speaks directly to the AI Specialist role. Highlight relevant experience, especially in AI systems and workflows, and don’t forget to showcase your collaboration skills with design and engineering teams.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in architecture and how your background makes you a perfect fit for Woods Bagot. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any AI projects or systems, make sure to include them in your application. Provide links or descriptions that demonstrate your hands-on experience and the impact of your work.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Woods Bagot
✨Know Your AI Stuff
Make sure you brush up on your AI knowledge, especially around multi-agent workflows and retrieval-augmented generation. Be ready to discuss your past experiences with AI systems and how they relate to the role at Woods Bagot.
✨Showcase Your Collaboration Skills
This role involves working closely with designers and project leaders, so highlight your teamwork experience. Prepare examples of how you've successfully communicated complex ideas to both technical and non-technical audiences.
✨Prepare for Practical Problem-Solving
Expect to tackle real-world design and operational problems during the interview. Think about how you would translate ambiguous issues into clear, testable system behaviours and be ready to share your thought process.
✨Demonstrate Your Adaptability
Woods Bagot values learning and growth, so be prepared to discuss how you've adapted to new tools and techniques in your previous roles. Share specific instances where you quickly learned something new and applied it effectively.