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- Tasks: Lead the design of innovative search and AI retrieval systems to enhance user experience.
- Company: Join a forward-thinking company dedicated to knowledge discovery and impactful decision-making.
- Benefits: Enjoy competitive perks like health insurance, extra holidays, and fun corporate events.
- Why this job: Be at the forefront of cutting-edge technology and make a real difference in how knowledge is accessed.
- Qualifications: 5+ years in search systems, strong Python skills, and experience with cloud-native technologies.
- Other info: Inclusive workplace encouraging diverse applicants to apply, even if they don't meet every requirement.
The predicted salary is between 80000 - 100000 ÂŁ per year.
Every day, somewhere in the world, important decisions are made. Whether it is a private equity company deciding to invest millions into a business or a large corporation implementing a new strategic direction, these decisions impact employees, customers, and other stakeholders. Consulting and private equity firms come to proSapient when they need to discover knowledge to help them make great decisions and succeed in their goals. It is our mission to support them in their discovery of knowledge.
We help our clients find industry experts who can provide their knowledge via interview or survey: we curate this knowledge in a market‑leading software platform; and we help clients surface knowledge they already have through expansive knowledge management.
As our Search & AI Retrieval Lead, you’ll define how structured data, semantic understanding, and intelligent systems come together to power discovery across our platform. From knowledge graphs to LLM‑driven enrichment and recommendation systems, you’ll be at the forefront of building something genuinely cutting‑edge—with real impact on how our users experience and navigate information.
Key Duties of this role will include:
- Search Architecture Strategy
- Evaluate and define the future search stack (technology selection is part of the role).
- Design a scalable, cloud‑native search architecture from first principles.
- Decide between and combine approaches such as:
- Keyword search
- Vector search
- Hybrid retrieval
- Graph‑based retrieval
- LLM re‑ranking
- Design indexing, data modeling, and ranking strategies.
- Define measurable relevance and quality frameworks.
- Design and implement a Knowledge Graph architecture modelling entities and relationships.
- Define graph schema, linking strategies, and enrichment workflows.
- Combine graph‑based signals with semantic search and ranking models.
- Build extraction pipelines on top of frontier models (OpenAI, Gemini).
- Develop modern recommendation systems leveraging structured + unstructured data.
- Architect retrieval pipelines on Google Cloud Platform (GCP).
- Design data pipelines and feature stores using BigQuery or alternative analytical systems.
- Ensure scalability, observability, and cost efficiency.
- Build production‑grade systems, not experiments.
Qualifications
- 5+ years building and scaling production search or retrieval systems.
- Strong experience designing search architectures, not just operating them.
- Experience evaluating and selecting search technologies.
- Experience with semantic search and embeddings‑based retrieval.
- Experience building pipelines on top of frontier LLMs (OpenAI, Gemini).
- Strong Python skills.
- Experience leading technical initiatives in mid‑sized teams.
- Experience working with cloud‑native systems (preferably GCP).
Benefits
- Tenure Gifts — Vouchers, extra holiday and sabbaticals for each year of employment.
- Health insurance through Vitality.
- Employee Assistance Programme – Access to a health and wellbeing service that offers personalised advice and support from specialist teams.
- Enhanced Maternity & Paternity pay.
- Annual Leave – 25 days + bank holidays which includes a week’s closure over the Christmas period to fully reset.
- MyMindPal app – Online support for mental fitness that helps people to stress less and enjoy life more.
- Corporate Events – From quarterly gatherings to our annual winter & Summer parties, we love to celebrate, collaborate and have fun together!
We are committed to building an inclusive workplace – did you know that marginalized groups are less likely to apply to jobs unless they meet every requirement listed? If you are interested in the above role, but don’t necessarily tick every box, we encourage you to apply anyway – this role could still be a great match!
Search & AI Retrieval Lead employer: proSapient
Contact Detail:
proSapient Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Search & AI Retrieval Lead
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend relevant events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or a project that highlights your expertise in search architecture and AI retrieval. This will not only demonstrate your capabilities but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for interviews by researching the company and its tech stack. Understand their challenges and think about how you can contribute to their goals. Tailor your answers to show how your experience aligns with their needs.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and engaged with our mission.
We think you need these skills to ace Search & AI Retrieval Lead
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Search & AI Retrieval Lead role. Highlight your experience with search architectures and retrieval systems, as well as any relevant projects that showcase your skills in semantic search and LLMs.
Showcase Your Technical Skills: We want to see your strong Python skills and experience with cloud-native systems like GCP. Include specific examples of how you've built or scaled production search systems, and don't forget to mention any technologies you've evaluated or selected.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make your achievements stand out. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website: We encourage you to apply directly through our website. This way, we can ensure your application gets the attention it deserves. Plus, it’s the best way to stay updated on your application status!
How to prepare for a job interview at proSapient
✨Know Your Tech Stack
Make sure you’re familiar with the latest search technologies and architectures. Brush up on your knowledge of keyword search, vector search, and LLM-driven systems. Being able to discuss these in detail will show that you’re not just a user but someone who understands the intricacies of the tech.
✨Showcase Your Experience
Prepare specific examples from your past roles where you’ve designed or scaled search systems. Highlight your experience with cloud-native systems, especially GCP, and how you’ve tackled challenges in building production-grade systems. Real-world examples will make your skills more tangible.
✨Understand the Business Impact
Since the role is about making informed decisions for clients, be ready to discuss how your work in search and AI retrieval can directly impact business outcomes. Think about how effective knowledge discovery can influence strategic decisions and be prepared to share your insights.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s current search architecture and future plans. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.