Senior Data & Integration Engineer (AI Platforms & Salesforce Ecosystem)

Senior Data & Integration Engineer (AI Platforms & Salesforce Ecosystem)
Overview

We are seeking a Senior Data & Integration Engineer to design, build, and scale AI-driven products and data integrations across our platform, with Salesforce as a key system within a broader ecosystem. This is not a traditional Salesforce development role — the focus is on integrating systems, enabling data flow, and supporting AI-native applications.

This role combines backend engineering, data engineering, and AI integration. You will work across systems to deliver scalable, reliable, and observable solutions that power both internal and customer-facing products.

Key Responsibilities

• Design and build scalable backend services (primarily Python) to support AI-driven products and integrations

• Develop and maintain integrations between Salesforce and other enterprise systems (e.g. Workday, ServiceNow, financial platforms)

• Build and optimise ETL pipelines, data workflows, and event-driven architectures

• Enable AI/ML use cases by supporting data pipelines, retrieval systems (RAG), and embedding workflows

• Integrate AI capabilities into complex workflows with a focus on reliability, auditability, and performance

• Collaborate with Product, Data, and Engineering teams to translate business problems into scalable technical solutions

• Implement observability (logging, metrics, tracing) and ensure production-grade reliability

• Contribute to architecture decisions across data, integration, and AI platforms

• Mentor junior engineers and promote engineering best practices

Required Skills & Experience

• Strong backend engineering experience (Python preferred)

• Proven experience in data engineering: SQL, ETL pipelines, and large-scale data processing

• Hands-on experience integrating SaaS platforms (Salesforce experience required, but not limited to internal platform development)

• Experience working with APIs, microservices, and event-driven architectures

• Exposure to modern data stacks (e.g. Airflow, dbt, Spark, or similar)

• Experience with cloud platforms (Azure preferred)

• Familiarity with AI/ML systems, including GenAI tooling (RAG, embeddings, evaluation frameworks)

• Strong understanding of system design, scalability, and observability

Desirable Skills

• Experience with vector databases and data retrieval systems

• Exposure to machine learning workflows or data science collaboration

• Frontend experience (React/Angular) for full-stack contributions

• Experience optimising performance, latency, and cost in AI systems

The ideal candidate will:

• Be comfortable working across multiple systems and data environments
  Have strong SQL and data pipeline experience

• Be able to integrate Salesforce into a wider architecture (not build exclusively within it)Bring curiosity and adaptability across AI, data, and engineering domains

Why Join

This is an opportunity to work on cutting-edge AI products while solving complex data and integration challenges at scale. You will play a key role in shaping how systems connect, how data flows, and how AI is embedded into real-world applications.

Whatever your career journey, we’ll help you find the right path. Through our training courses, mentorship, and continuous support, you’ll get everything you need to thrive. At Epicor, your success is our success. And that success really matters, because we’re the essential partners for the world’s most essential businesses—the hardworking companies who make, move, and sell the things the world needs.

Recruiter:

Kai Lewis