At a Glance
- Tasks: Design and optimise AI-driven data pipelines for Salesforce Service Cloud.
- Company: Leading finance sector company with a focus on innovation.
- Benefits: Competitive market rate, hybrid working, and professional development opportunities.
- Other info: Exciting role with potential for career growth in a regulated environment.
- Why this job: Join a dynamic team and work with cutting-edge AI technologies.
- Qualifications: 5-10 years in Data Engineering/AI Engineering with strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
6-Month contract – Inside IR35 – market rate London based – hybrid working – up to 3 days a week onsite.
Finance sector - must have previous experience.
Role Overview
Senior AI / Data Engineer responsible for designing, building, and optimizing AI-driven data pipelines and integrations to enable a QAS-powered response suggestion capability embedded in Salesforce Service Cloud. The role focuses on scalable data processing, LLM integration, and continuous model improvement using production telemetry.
Responsibilities
- Design and implement Salesforce QAS integration architecture
- Build and optimize data pipelines supporting AI inference and feedback loops
- Integrate LLM capabilities (Amazon Bedrock) for response generation and embeddings telemetry data quality scoring usage analytics
- Work with structured and unstructured data sources: Microsoft Graph (SharePoint / Teams)
- Ensure data reliability, scalability, and performance
- Contribute to: Support: SIT/UAT phases production readiness hypercare and rollout to additional entities
Required Experience & Skills
- 5–10 years of experience in Data Engineering / AI Engineering
- Strong experience in: Python / JVM-based backend development, REST APIs / microservices
- Experience with cloud-native architectures on AWS
- Hands-on with: data pipelines (batch + streaming), embeddings / retrieval architectures
- Experience using: Snowflake (data platform integration, CDC concepts)
- AWS Stack: S3, RDS, SQS, EventBridge
- Containerized workloads (EKS/ECS)
- Strong understanding of: distributed systems, performance optimization, observability (e.g. Langfuse, logging/metrics)
Nice-to-Have
- Experience with: Salesforce Service Cloud integrations, NLP / GenAI applications in customer service
- Exposure to: Amplitude or product analytics tools
- Knowledge of regulated environments (banking / capital markets)
Soft Skills
- Ability to work in cross-functional distributed teams
- Clear communication with business and technical stakeholders
AI Application/Big Data Engineer employer: Advanced Resource Managers
As a leading player in the finance sector, we offer an exceptional work environment that fosters innovation and collaboration. Our hybrid working model allows for flexibility, while our commitment to employee growth ensures that you will have access to continuous learning opportunities and cutting-edge projects. Join us in London, where you can make a meaningful impact on AI-driven solutions within a supportive and dynamic team culture.
Contact Details:
Advanced Resource Managers Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Application/Big Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance sector and let them know you're on the hunt for an AI Application/Big Data Engineer role. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Get your online presence sorted! Make sure your LinkedIn profile is up-to-date and showcases your experience with data pipelines, AI engineering, and cloud-native architectures. Recruiters often search for candidates there, so let’s make sure you shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of Salesforce Service Cloud integrations and AWS stack. Be ready to discuss your hands-on experience with Python and data processing, as these are key to landing that contract.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace AI Application/Big Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Application/Big Data Engineer role. Highlight your experience with data pipelines, LLM integration, and any relevant projects that showcase your skills in Python and AWS. We want to see how your background fits our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your previous experience aligns with our requirements. Be sure to mention any specific projects or achievements that demonstrate your expertise in AI and data engineering.
Showcase Relevant Skills:When filling out your application, make sure to highlight your hands-on experience with tools like Snowflake and AWS services. We’re looking for someone who can hit the ground running, so don’t be shy about showcasing your technical skills and any relevant certifications!
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 gives you a chance to explore more about StudySmarter and what we stand for!
How to prepare for a job interview at Advanced Resource Managers
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in Python and AWS. Be ready to discuss your experience with data pipelines and LLM integration, as these are crucial for the role. Prepare to share specific examples of projects where you've optimised data processing or built scalable architectures.
✨Understand the Finance Sector
Since this role is in the finance sector, it’s important to familiarise yourself with industry-specific challenges and regulations. Research how AI and data engineering are being used in banking and capital markets, and be prepared to discuss how your skills can address these needs.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think about how you would approach integrating Salesforce QAS or handling unstructured data sources. Practising these scenarios will help you articulate your thought process clearly during the interview.
✨Showcase Your Soft Skills
Don’t forget to highlight your soft skills! Communication is key, especially when working with cross-functional teams. Be ready to provide examples of how you've effectively communicated complex technical concepts to non-technical stakeholders in previous roles.
