The Role:
The VP of Engineering is the technical authority at Forsys. You will lead our global Salesforce development and data engineering teams, setting the architectural standards, engineering practices, and AI tooling culture that define how we build. You are expected to be deeply hands-on this is a player-coach role where your credibility comes from what you know and what you can do, not just your title. That means pairing with architects on hard problems, reviewing code, getting into Salesforce orgs when delivery is at risk, and personally using the AI tools you'll be asking your team to adopt. If you haven't opened a Salesforce org or written a prompt this week, this is not the right role for you.
Forsys is moving to an AI-first delivery model, and this role leads that shift from the front. You don't need to be a trained AI engineer but you must be someone who has already started building with AI tools, who is genuinely excited about what vibe coding and AI-augmented development unlock for engineering teams, and who can credibly lead developers through that transition.
What You Will Do
Engineering Leadership & Team Development
- Lead, manage, and scale Forsys's global Salesforce development and data engineering teams. Build high-performing squads that excel in execution, code quality, and innovation.
- Define career paths, engineering competency frameworks, and mentorship programs that develop our developers especially as AI tools reshape what great engineering looks like.
- Partner with the VP of Projects and delivery leadership to ensure development teams are aligned to project outcomes, not just ticket completion.
AI Tooling Adoption & Developer Experience (DevEx)
- Lead the rollout of AI-assisted development tools Cursor, Claude Code, and GitHub Copilot across Forsys's engineering organization. Make AI-augmented development the default workflow, not an optional experiment.
- Work with Forsys leadership to evaluate and adopt AI infrastructure appropriate to a Salesforce consulting firm including how tools like Claude and Agentforce integrate into client delivery workflows.
- Model AI-first development personally. You should be someone who already uses vibe coding tools daily and can demonstrate their value concretely to skeptical engineers and technical architects.
- Establish engineering standards for AI-generated code review practices, quality gates, and governance guidelines that ensure AI-assisted output meets Forsys's delivery standards.
Technical Architecture & Standards
- Serve as the final technical authority on complex Salesforce architecture decisions Apex, LWC, Platform Events, integration patterns, data model design, and release management.
- Define Forsys's architectural standards for Salesforce integrations (ERP/CRM, middleware, REST/SOAP, and event-driven architectures) and data migration strategies.
- Conduct architecture reviews on high-stakes engagements, ensuring technical decisions are scalable, maintainable, and aligned to Salesforce best practices.
Agentic AI & Innovation
- Stay ahead of the Agentforce platform evolution, evaluating new capabilities as Salesforce releases them and defining where and how Forsys incorporates them into delivery.
- Collaborate with the VP of Projects to define how AI tools change the project lifecycle faster prototyping, AI-assisted requirements validation, automated testing and what that means for how engineering teams are structured and measured.
- Identify and explore emerging AI capabilities (Agentforce, Einstein features, AI-assisted data migration) that can differentiate Forsys's delivery or be productized as client-facing IP.
Experience:
- 10+ years leading Salesforce engineering teams, ideally in a consulting or systems integration environment where you managed multiple concurrent client engagements.
- Proven track record building and scaling distributed engineering teams hiring senior architects, establishing engineering culture, and driving technical accountability.
- Experience delivering complex Salesforce implementations involving multi-cloud setups, ERP integrations, data migrations, and high-volume transaction processing.
Salesforce Technical Mastery
- Deeply hands-on with Apex, LWC (Lightning Web Components), Salesforce Integration Cloud, and the broader Salesforce DevOps toolchain (SFDX, Copado, Gearset, or equivalent).
- Strong architectural command of Salesforce platform limits, governor limits, data modeling, sharing and visibility, and release management at scale.
- Experience with Agentforce, Einstein features, or Salesforce Data Cloud is highly valued.
- Salesforce certifications (Application Architect, System Architect, or CTA) are a strong signal though demonstrated hands-on depth matters more.
AI Curiosity & Practical Experience
- You don't need a formal AI engineering background but you must have already started building with AI tools in a meaningful way. That might mean you've built a working Agentforce flow, integrated Claude or another LLM API into a Salesforce workflow, or are actively using Cursor or Claude Code as part of how you develop and prototype.
- You have a genuine point of view on how AI changes software development not borrowed from conference talks, but formed through hands-on experimentation.
- You are excited about vibe coding and what it means for engineering team productivity. You see AI-augmented development as the future of how Forsys's developers work, and you want to lead that shift.
- Familiarity with MCP (Model Context Protocol), Agentforce, or similar Salesforce AI tooling is a meaningful differentiator but demonstrated curiosity and momentum matter more than depth.
Leadership & Mindset
- A genuine player-coach: technically credible enough to pair with a senior architect on a complex Salesforce problem, and strategically grounded enough to run a multi-team engineering organization of 80+ developers.
- Strong communicator who can translate complex technical decisions for executive stakeholders clients and internal leadership alike.
- Passionate about engineering excellence, developer experience, and building a culture where AI tools amplify what great engineers can do not replace the judgment and accountability that makes engineering trustworthy.
- Comfortable operating in a consulting environment where priorities shift, clients have opinions, and the ability to deliver high-quality work under pressure is non-negotiable.
- Not threatened by AI energised by it. The right person sees vibe coding and AI-augmented development as the most interesting shift in software engineering in a decade, and wants to be at the front of that wave.
