About this role
We are seeking a senior, hands-on Salesforce engineer who can design and deliver secure solutions while coaching and influencing across teams. You will own end-to-end technical execution (design through production support), support architectural evaluations with internal and external partners, and help modernize platforms through automation, optimization, and capabilities including AI/LLM and Agentforce .
Key Responsibilities
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Design, develop, and troubleshoot software solutions; break down complex technical problems using practical, effective approaches.
- Build secure, production-grade code; review, debug, and improve code written by others.
- Identify recurring issues and implement elimination/automation strategies to improve the operational stability of applications and systems.
- Participate in evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and fit within the enterprise information architecture.
- Contribute to communities of practice to drive awareness and adoption of emerging technologies across software engineering.
- Contribute to a team culture rooted in diversity, equity, inclusion, and respect.
Required Qualifications (Must Have)
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.
- Senior-level engineering experience with demonstrated coaching/mentorship, while remaining hands-on.
- 5+ years of Salesforce development experience , including deep expertise in:
- Agentforce and AI/LLM-related capabilities/use cases
- Apex
- Lightning Web Components (LWC)
- Triggers, Flows
- Sales Cloud, Service Cloud, Financial Services Cloud (FSC)
- REST APIs, web callouts/integrations
- Strong communication skills and executive presence; able to explain technical details clearly, including how systems work end-to-end and why design decisions were made.
- Proven experience handling large data volumes, performance tuning, and platform/application optimizations.
Preferred Qualifications (Nice to Have)
- Financial services industry experience.
- Experience building or integrating cloud-native applications.
- AWS experience.
- Java experience.
- Familiarity with Jira, Bitbucket, and source control/version control systems.
What Success Looks Like
- Releases delivered reliably with measurable improvements in stability and performance.
- Strong design decisions, effective code reviews, and active coaching that raises team capability.
- Scalable Salesforce solutions aligned to enterprise architecture and integration standards.