Job Title: Salesforce Principal Engineer
Job Type: Contract · Inside IR35
Location: Windsor, UK — Hybrid (1 day a week)
Duration: 6 months
Job Purpose and primary objectives
- Key responsibilities (please specify if the position is an individual one or part of a team):
- Provide technical leadership and architectural direction to salesforce developers and business stakeholders
- Define and own salesforce system architecture, standards, patterns, and guardrails across APIs, integration layers, and platform services
- Shape and deliver new mobile capabilities that improve safety, compliance, customer experience, and field productivity
- Champion engineering excellence including clean architecture, CI/CD automation, testing strategies, observability, release processes, performance optimisation, and secure-by-design practices
- Ensure platform reliability, resilience, and strong technical understanding
- Continuously improve ways of working through automation and AI-enabled tooling, while retaining human accountability for technical decisions
Key Skills/Knowledge
- Strong technical expertise in Salesforce – service cloud, E&U cloud preferred.
- Deep understanding of LWC, APEX, Flows and API developments
- Proven experience defining and influencing engineering standards, coding practices, and architectural guardrails across multiple teams
- Strong knowledge of CI/CD pipelines- Github knowledge and deployment experience.
- Ability to solve complex, ambiguous, cross-domain technical problems
- Working knowledge of AI-enabled engineering practices
Experience required
- Significant experience as a Senior or Principal Software Engineer within complex digital or platform-based environments and Salesforce service cloud with some industry cloud knowledge.
- Experience influencing technical direction across multiple teams without direct line management responsibility
- Degree in Computer Science, Engineering, or equivalent practical experience
- Experience operating within established architectural frameworks, security standards, and data privacy requirements
- Ability to design, integrate and operate AI‑enabled solutions within enterprise environments, including prompt‑driven workflows, retrieval‑augmented systems and AI agents. Applying structured evaluation, testing and monitoring practices to ensure AI outputs are reliable, secure and compliant with organisational guardrails.
- Prepares and manages data used in AI workflows and take responsibility for the responsible lifecycle of AI features from experimentation through to deployment and continuous improvement.
- I.e., Negotiating, client facing, communication, assertive, team leading/team member skills, supportive.
- Client Facing, Excellent communication, Team leadership, Co-ordination, and multiple vendor engagement
