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- Tasks: Transform human expertise into explainable AI solutions using our low-code platform.
- Company: Join Rainbird, a leader in redefining the future of explainable AI.
- Benefits: Enjoy competitive pay, generous holidays, and a remote-first culture.
- Why this job: Make a real impact by solving complex business problems with cutting-edge technology.
- Qualifications: 2-4 years in consulting or business analysis with strong analytical skills.
- Other info: Collaborate with a curious global team and accelerate your career in AI.
The predicted salary is between 43200 - 72000 £ per year.
Join Rainbird as a Senior Knowledge Engineer, and transform human expertise into explainable, trustworthy AI solutions. Using our low-code decision intelligence platform, you'll rapidly build AI models that deliver clarity and confidence at scale, empowering clients across industries. Collaborate, innovate, and shape the future of AI-driven decision-making.
Contract Type: Permanent, Full Time
Location: London – Hybrid – with flexibility to work with global clients
Package: Competitive, based on experience
About Rainbird
Rainbird is redefining the future of explainable AI. Our platform enables organisations to build deterministic, transparent decision-automation systems for industries where accuracy, trust, and accountability matter most – including healthcare, banking, insurance, and professional services. At the heart of Rainbird is a symbolic reasoning engine that makes every automated decision fully transparent, auditable, and justifiable. We empower enterprises to scale their expertise, combining human insight with machine precision. We're growing fast in the UK and US, and this is an opportunity to join a mission-driven team shaping the future of trusted AI.
Why Rainbird?
- Impactful work: Help some of the world's biggest enterprises solve complex, high-stakes business problems.
- Cutting-edge technology: Work at the intersection of symbolic reasoning, large language models, and explainable AI.
- Growth & learning: Accelerate your career with hands-on experience in knowledge modelling, decision automation, and hybrid AI.
- Remote-first culture: Work flexibly from anywhere, supported by a collaborative, inclusive, and curious global team.
- Great benefits: Competitive pay, generous holiday allowance and opportunities to lead in a rapidly expanding company.
Role Specification
As a Senior Knowledge Engineer, you'll play a pivotal role in capturing expert knowledge from clients and transforming it into intelligent, transparent decisioning systems using the Rainbird platform. This is a hands-on, hybrid role: part business analyst, part solution builder. You'll work directly with client stakeholders to analyse complex decision processes, translate them into structured logic, and build auditable reasoning systems within the Rainbird Studio. This role is ideal for someone who thrives on solving complex problems, enjoys working closely with clients, and has a passion for turning human expertise into scalable, intelligent systems.
Key Responsibilities
- Client Engagement & Analysis: Understand client decision-making and challenges. Capture knowledge via analysis/workshops/interviews. Bridge business and technical teams.
- Solution Implementation & Delivery: Lead end-to-end Rainbird implementations. Build reasoning graphs, workflows, and tests. Define/document functional requirements.
- Knowledge Capture & Modeling: Extract decision logic from experts/docs. Translate into and refine Rainbird graphs. Maintain governance and scalability. Act as Rainbird expert/champion. Create reusable components and tools. Improve methodology and contribute best practices.
- Team Contribution: Align business/technical discussions. Lead training and knowledge sharing.
Qualifications
- 2–4 years' experience in a consulting, implementation, or business analysis role with direct client engagement and requirements gathering.
- Experience delivering or supporting software implementations within an enterprise environment.
- Strong understanding of Large Language Models and prompt-engineering principles.
- Excellent analytical and problem-solving skills, including debugging complex logic.
- Clear communicator able to engage confidently with both technical and non-technical stakeholders.
- Highly organised and self-motivated, capable of supporting multiple client projects simultaneously.
Preferred
- Ability to read and manipulate structured data formats such as JSON and XML.
- Experience with rules engines, decision management systems, or BPM/low code platforms.
- Knowledge of formal logic, knowledge representation, or semantic technologies (RDF, OWL, SPARQL).
- Familiarity with machine-learning concepts and how probabilistic methods complement deterministic reasoning.
- Domain experience in banking, financial services, insurance, healthcare, or other highly regulated industries.
- Degree in a logic, analytical, or consulting-oriented field such as Cognitive Science, AI, Mathematics, Information Systems, Engineering, or Business Analysis (or equivalent experience).
What Success Looks Like
- Project Delivery: Consistent on-time delivery of client implementations' tasks, meeting defined scope and quality standards.
- Client outcomes: Deliver high-quality solutions that meet client goals and build long-term relationships.
- Solution quality: Models are transparent, accurate, maintainable, and auditable.
- Innovation: Contribute to accelerators and best practices that improve how Rainbird delivers projects.
- Knowledge sharing: Mentor colleagues and empower client teams to maintain and evolve their Rainbird solutions.
- AI Model Integrity: Maintainable, well-structured knowledge graphs and supporting artefacts, adhering to internal quality benchmarks.
- Reusability & Innovation: Contribution to reusable components, accelerators, and platform enhancements that improve delivery efficiency.
Rainbird is an equal opportunities employer.
Senior Knowledge Engineer in England employer: Rainbird Technologies
Contact Detail:
Rainbird Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Knowledge Engineer in England
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a project that highlights your expertise in AI and decision-making. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to knowledge engineering. The more you rehearse, the more confident you'll feel when it’s showtime!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people at Rainbird. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Knowledge Engineer in England
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Knowledge Engineer role. Highlight your experience with decision-making processes and any relevant projects that showcase your skills in AI and client engagement.
Showcase Your Problem-Solving Skills: We love candidates who can think on their feet! Use your application to demonstrate how you've tackled complex problems in the past, especially in a consulting or implementation context. Real-life examples will make you stand out!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and how it aligns with our mission at Rainbird. Avoid jargon unless it's necessary, and make sure your key points shine through.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Rainbird Technologies
✨Know Your Stuff
Before the interview, dive deep into Rainbird's platform and its applications in explainable AI. Familiarise yourself with symbolic reasoning, decision automation, and how these technologies are used across industries like healthcare and banking. This knowledge will help you speak confidently about how your skills align with their needs.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples from your past experience where you've tackled complex problems. Think about how you captured expert knowledge or built decision-making systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate your analytical prowess.
✨Engage with Clients
Since client engagement is key for this role, be ready to talk about your experience working directly with clients. Highlight how you've bridged the gap between technical and non-technical teams, and share any successful strategies you've used to gather requirements and deliver solutions that meet client goals.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare thoughtful questions that show your interest in Rainbird's mission and culture. Ask about their approach to innovation in AI, how they support team collaboration in a hybrid environment, or what success looks like for a Senior Knowledge Engineer in their eyes. This not only shows your enthusiasm but also helps you gauge if it's the right fit for you.
