Salesforce AI Engineer: Build AI-Driven Enterprise Apps

CAPGEMINI; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working

Wellbeing & Diversity Programs

Training & certifications

Disability Confident Employer

Job summary

Capgemini UK is seeking a Salesforce AI Engineer to design, build and ship AI features on the Salesforce platform for leading organisations. You will work hands-on with Agentforce, Einstein, Prompt Builder, Model Builder and Data Cloud to create AI-driven Salesforce solutions that perform under real workloads.

You'll collaborate with consultants and architects to translate business needs into scalable technical designs, implement declarative and programmatic solutions, and drive DevOps practices

Qualifications

• Strong Salesforce technical experience across core clouds including Sales Cloud, Service Cloud, Experience Cloud, Commerce Cloud, Industries Cloud, or Field Service.
• Hands-on experience developing solutions using Apex, Lightning Web Components (LWC), Flow, JavaScript, APIs, and Salesforce integration patterns.
• Hands-on experience building with Agentforce, Einstein, Prompt Builder and Model Builder, including designing agent actions, writing and tuning prompts, and grounding models in Salesforce data.
• Working understanding of prompt engineering, retrieval-augmented generation (RAG), grounding, and how to reduce hallucination.
• Experience testing and evaluating AI features, measuring accuracy, and monitoring quality, cost and latency once live.
• Knowledge of enterprise integration approaches, including MuleSoft, event-driven architectures, REST/SOAP APIs, and external system connectivity.
• Experience building solutions for large-scale environments supporting hundreds or thousands of Salesforce users.
• Nice to have: MCP, vector search and embeddings, or Python for AI tooling.

Responsibilities

• Partner with Salesforce Functional Consultants, Solution Architects, and AI Specialists to design and deliver innovative Salesforce and AI-powered business solutions.
• Leverage Agentforce, Einstein, Prompt Builder, Model Builder, and Data Cloud to develop intelligent experiences, autonomous agents, and AI-augmented business processes.
• Act as a Salesforce and AI subject‑matter expert within the DCX practice, helping shape next‑generation consulting capabilities and AI delivery methodologies.
• Design and develop scalable Salesforce solutions using Apex, Lightning Web Components (LWC), Flow, JavaScript, Platform Events, and APIs.
• Build AI‑enabled solutions that combine customer, operational, and enterprise data to deliver personalised, predictive, and proactive business experiences.
• Integrate Salesforce with enterprise systems using MuleSoft, APIs, Event‑Driven Architectures, and AppExchange solutions to create connected digital ecosystems.
• Utilise AI‑assisted development tools and modern DevOps practices to accelerate delivery, increase quality, and improve developer productivity.
• Contribute to continuous innovation by evaluating emerging Salesforce AI capabilities and identifying opportunities to apply them across client engagements.
• Support Agile delivery teams and champion modern engineering practices using Gearset, Copado, Flosum, GitHub, Azure DevOps, and CI/CD pipelines.
• Engage directly with client stakeholders, helping them understand how AI, automation, and Salesforce technology can unlock measurable business value.

Skills

Salesforce Apex & LWC

Agentforce & Einstein

APIs & Integration

Prompt Engineering

DevOps & CI/CD

LLMs & AI tooling

Large Language Models

Tools

MuleSoft

Gearset

Copado

Flosum

GitHub

Azure DevOps

Job description

Capgemini UK is seeking a Salesforce AI Engineer to design, build and ship AI features on the Salesforce platform for leading organisations. You will work hands-on with Agentforce, Einstein, Prompt Builder, Model Builder and Data Cloud to create AI-driven Salesforce solutions that perform under real workloads.

You'll collaborate with consultants and architects to translate business needs into scalable technical designs, implement declarative and programmatic solutions, and drive DevOps practices