AI Application/Big Data Engineer

AI Application/Big Data Engineer in London

Location

London

Salary

Negotiable

Contract

Contract

AI Application/Big Data Engineer

6-Month contract - Inside IR35 - market rate

London based - hybrid working - up to 3 days a week onsite

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
• Experience with 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
• Containerized workloads (EKS/ECS)

Engineering Practices

• 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
• Strong ownership mindset (design production)
• Clear communication with business and technical stakeholders