At a Glance
- Tasks: Build transformative AI capabilities and develop end-to-end GenAI features.
- Company: Join Anaplan, a leader in AI-infused business planning solutions.
- Benefits: Inclusive culture, career growth, and the chance to work with top global brands.
- Other info: Diverse and inclusive workplace committed to your authentic self.
- Why this job: Make a real impact on how businesses plan and make decisions with cutting-edge technology.
- Qualifications: Extensive data engineering experience and hands-on AI/ML product development skills.
The predicted salary is between 70000 - 90000 £ per year.
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in‑class platform.
We're seeking a Senior Data Engineer to work across the full stack of Anaplan AI applications. You will build transformative AI capabilities from the ground up, from model integration and prompt engineering to contributing to the technical direction for how we ingest, transform, store, serve, and govern the data that powers our LLM‑based and agentic systems. You will build user‑facing AI features that can be used in real‑time, directly impacting how businesses plan and make decisions. This role requires both a strong foundation in machine learning and excellent data engineering skills, offering a unique opportunity to grow at the intersection of AI and enterprise software.
Your Impact
- Contribute to the data architecture, design, and deployment of scalable Generative AI and Machine Learning systems into production environments.
- Develop end‑to‑end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments.
- Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering and RAG implementation.
- Design and build the retrieval and knowledge layer powering our RAG and agentic workloads, such as vector databases, graph databases, knowledge graphs, hybrid search, and embedding pipelines.
- Help design the knowledge graph that captures the semantics of customer models, metrics, hierarchies, and relationships.
- Build the data plane for evaluation and continuous improvement, working with cutting‑edge conversational and agentic AI technologies.
- Engineer the feature and context pipelines that feed forecasting and anomaly‑detection models at customer scale, balancing batch and streaming patterns.
- Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics.
Your Skills
- Extensive data engineering experience with a track record of delivering complex projects.
- Hands‑on experience building and shipping AI/ML products in production.
- Practical experience with LLM‑based systems: RAG architectures, embedding pipelines, prompt and response logging, and evaluation frameworks.
- Hands‑on expertise with vector databases, graph databases, and knowledge graphs.
- End‑to‑end exposure to the model development lifecycle, including experience training and deploying ML models in production environments.
- Solid knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Hands‑on experience with cloud‑native ML infrastructure platforms.
- Knowledge of vector databases (e.g., Pinecone, Weaviate, Qdrant) and embedding models.
- Experience with model serving frameworks (e.g., vLLM, TensorRT, Ray).
- Background in forecasting, planning, or analytics applications.
- Experience with A/B testing and experimentation frameworks for AI features.
- Experience with model observability tools (e.g., LangSmith, W&B, MLflow).
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Senior Data Engineer - AI employer: Anaplan Inc
At Anaplan, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the heart of the tech industry. Our commitment to a Winning Culture fosters a supportive environment where employees can thrive, with ample opportunities for professional growth and development in cutting-edge AI technologies. Join us in a diverse and inclusive workplace that values your unique contributions and empowers you to make a real impact on global business decision-making.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - AI
✨Tip Number 1
Network like a pro! Reach out to current employees at Anaplan on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. It’s all about making connections!
✨Tip Number 2
Prepare for technical interviews by brushing up on your data engineering skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 3
Showcase your passion for AI and data engineering during interviews. Share your thoughts on industry trends and how you can contribute to Anaplan's mission. Let your enthusiasm shine through!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Anaplan.
We think you need these skills to ace Senior Data Engineer - AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your data engineering and AI/ML project experience, and don’t forget to mention any hands-on work with LLMs or cloud-native ML infrastructure.
Craft a Compelling Cover Letter:Your cover letter is your chance to show us your personality and passion for the role. Share specific examples of how you've contributed to similar projects in the past and why you're excited about working with Anaplan's innovative AI solutions.
Showcase Your Technical Skills:In your application, be sure to highlight your proficiency in Python and any relevant tools or frameworks you've used. We want to see your hands-on experience with vector databases, model serving frameworks, and MLOps practices.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Anaplan Inc
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around LLMs, vector databases, and MLOps. Brush up on your Python skills and be ready to discuss your hands-on experience with AI/ML products.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific projects where you've tackled complex data engineering challenges. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how your contributions made a real impact.
✨Understand the Business Context
Familiarise yourself with Anaplan’s platform and its applications in business planning. Be ready to explain how your technical skills can directly benefit their customers and improve decision-making processes.
✨Emphasise Collaboration and Culture Fit
Anaplan values a winning culture and teamwork. Be prepared to share examples of how you’ve worked effectively in teams, contributed to a positive work environment, and embraced diversity and inclusion in your previous roles.