Sr. Salesforce Platform Engineer - AI + Automation

The candidate will have responsibilities across the following functions:

Platform Architecture and Salesforce Ownership:

• Own end-to-end solution design and execution for the Salesforce platform, including data models, integration architecture, automation patterns, configuration, custom code, deployment, and maintenance.
• Make independent architectural decisions within established guardrails; collaborate with the internal architect on complex or cross-system decisions.
• Develop and maintain Apex classes, triggers, batch jobs, LWC, SOQL, and SFDX-based deployments.
• Own integration architecture and technical guidance across the full technology ecosystem, not limited to Salesforce.
• When any systems need to connect, this role defines how.
• Lead the technical configuration and integration of new systems brought into the environment, including those that interact with Salesforce and those that do not.
• Define and enforce technical standards, patterns, and best practices for the platform.

AI-Assisted Development and Automation:

• Use Claude, Claude Code, GitHub Copilot, Codex, and Agentforce as primary development instruments — automation-first engineering throughout the full SDLC.
• Follow a systematic AI development workflow: AI-assisted code generation → rigorous review and validation → automated testing → controlled CI/CD deployment. Never deploy AI-generated code straight to production.
• Build AI-driven workflows to eliminate manual tasks and measurably increase throughput across requirements, design, build, test, and release.
• Set and model the standard for responsible, systematic AI-assisted development across the team.

Change Control and DevOps:

• Own Git-based change control (GitHub, Bitbucket, or equivalent): branching, PR governance, code review standards, and release management for all Salesforce development.
• Build and maintain CI/CD pipelines with automated testing and deployment validation before changes reach production.
• Ensure all changes (configuration, code, and integrations) are version-controlled, traceable, and auditable.

Technical Leadership, Agile and Stakeholder Partnership:

• Serve as technical lead for QA testers and developers; manage the Systems Project Board and sprint flow.
• Partner with the internal architect for guidance and provide technical oversight for external developers as the team scales.
• Translate business requirements into sprint-ready technical solutions in partnership with the Product Manager.
• Must be available for U. S. stakeholder meetings during evening hours (IST), typically 6:00-9:00 PM IST, to maintain overlapping business hours with the U. S. team. Communicate status, risks, and dependencies proactively.
• Own the debugging and case board; scale into team management as QA and development resources grow.

Requirements:

• 5+ years of hands-on Salesforce experience — configuration AND development (Apex, LWC, SOQL, APIs, administration).
• 1+ year using AI coding tools (Claude / Claude Code, Codex, GitHub Copilot, or equivalent) with a systematic workflow: AI development → code review → automated testing → controlled deployment.
• Architect-level solution design — data modelling, integration architecture, platform standards.
• Broad system integration experience — REST APIs, OAuth 2.0, middleware, databases (SQL/NoSQL), and third-party platforms. Comfortable architecting integrations between any combination of systems, not limited to Salesforce.
• Git-based version control (GitHub, Bitbucket, or equivalent): branching, PR governance, Salesforce CI/CD.
• Experience directing or guiding QA testers and/or developers on technical deliverables.
• Active Agile participation — sprint planning, standups, backlog grooming, retrospectives.
• Salesforce certifications (Admin, Platform Developer I or II, Service Cloud, Experience Cloud).
• Salesforce Architect certification (Application Architect, System Architect, or CTA) — a plus, not required.
• Familiarity with JavaScript and Google Apps Script for Google Workspace integrations.

Tools and Platforms:

Candidates should be comfortable working across the following:

• Salesforce — Sales Cloud, Service Cloud, Experience Cloud, custom objects and integrations.
• Claude and Claude Code — primary AI development environment (enterprise license).
• Git-based version control — GitHub / Bitbucket, CI/CD pipelines, SFDX, Gearset or equivalent.
• Google Workspace — Drive, Gmail, Calendar, Apps Script integrations.
• Project management — Jira | Additional AI tooling — Codex, GitHub Copilot, Agentforce Agentic AI, LLMS, RAG, Etc.