AI Application/Big Data Engineer
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
- Develop backend services / APIs enabling response suggestion workflows
- Integrate LLM capabilities (Amazon Bedrock) for response generation and embeddings
- Enable continuous model tuning via telemetry data, quality scoring, usage analytics
- Work with structured and unstructured data sources: Microsoft Graph (SharePoint / Teams)
- Implement asynchronous processing pipelines (SQS, EventBridge)
- Ensure data reliability, scalability, and performance
- Contribute to design documentation, runbooks, technical decision-making
- Support SIT/UAT phases, production readiness, hypercare and rollout to additional entities
Required Experience & Skills
Core
- 5-10 years of experience in Data Engineering / AI Engineering
- Strong experience in Python / JVM-based backend development, REST APIs / microservices, cloud-native architectures on AWS Data & AI
- Hands‑on with Amazon Bedrock (or equivalent LLM platforms), data pipelines (batch + streaming), embeddings / retrieval architectures
- Experience using Snowflake (data platform integration, CDC concepts), PostgreSQL (RDS), AWS Stack – S3, RDS, SQS, EventBridge, containerised workloads (EKS/ECS) and engineering practices
- Strong understanding of distributed systems, performance optimisation, observability (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
- Strong ownership mindset (design → production)
- Clear communication with business and technical stakeholders
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