Senior Software Engineer II

About our Team:-

Digital Business Solutions (DBS) delivers innovation and solves customer and business problems by leveraging the power of technology, data, and — increasingly — AI. Within DBS, the AI Innovation team focuses specifically on identifying and delivering agentic and generative AI capabilities across our Salesforce ecosystem and adjacent platforms. We partner with sales teams to drive intelligent automation, frictionless personalized experiences, and streamlined processes that support cost optimization and growth. We provide the expertise to understand business challenges and translate them into practical, responsible AI-enabled solutions.

About the Role:-

This position performs complex research, design, and software development assignments within our Salesforce platform ecosystem (Sales Cloud, Service Cloud, CPQ, Experience Cloud, Revenue Cloud and adjacent integrated platforms), and provides direct input to project plans, schedules, and methodology in the development of cross-functional solutions serving 2,000+ users. This position performs software design across Salesforce org and integrated systems (e.g. Gainsight, Monday.com, Incentive Comp Platforms); mentors more-junior members of the team; leverages AI-assisted development tools to accelerate delivery and improve code quality; and talks to business users/stakeholders to translate their requests into scalable, compliant Salesforce solutions.

Responsibilities:-

• Interface with business analysts, platform admins, and other technical team members to finalize requirements across the Salesforce platform and its integrated ecosystem
• Write and review detailed technical specifications for complex system components, including custom Apex/LWC solutions and AI agent/automation designs
• Complete complex bug fixes across Apex, Lightning Web Components, Flow automation, and third-party integrations
• Work closely with other development team members to understand complex product requirements and translate them into scalable Salesforce architecture and software designs
• Successfully implement development processes, coding best practices, code reviews, and AI-assisted development standards (including responsible use, review, and validation of AI-generated code)
• Design, build, and govern AI-driven agents and automations on the platform (e.g., Agentforce), ensuring outputs are accurate, secure, and aligned with business processes
• Operate in various development environments (Agile, Waterfall, etc.) while collaborating with key stakeholders across sales technology teams
• Resolve complex technical issues across Salesforce and adjacent platforms (Oracle Sales Cloud Incentive Comp, Gainsight, Monday.com) as necessary
• Train and onboard entry-level software engineers, ensuring they are knowledgeable in Salesforce development standards and AI-assisted tooling as directed by department management
• Keep abreast of new Salesforce platform releases, AI feature developments, and evolving AI development tooling
• Design and work with complex Salesforce data models supporting a 2,000+ user org, including performance and scalability considerations
• Mentor less-senior software developers on Salesforce development methodologies, optimization techniques, and effective/responsible use of AI development tools
• Ensure development work aligns with release management, packaging, and compliance/audit requirements
• All other duties as assigned

Requirements:-

• Advanced knowledge of software development methodologies (Agile/Scrum, Waterfall) as applied to Salesforce release cycles and org governance
• Strong proficiency in Apex, SOQL/SOSL, and data manipulation/optimization techniques (bulkification, governor-limit-aware design, asynchronous processing patterns)
• Strong understanding of Salesforce data modeling: standard/custom objects, normalized vs. denormalized structures, sharing/security models, and large data volume (LDV) design
• Strong knowledge of Salesforce data storage and integration subsystems (Salesforce Connect, Platform Events, Change Data Capture, MuleSoft or equivalent middleware, external objects)
• Expertise in Salesforce development languages and frameworks: Apex, Lightning Web Components (LWC), Aura, JavaScript, SOQL/SOSL, Flow/Flow Orchestrator, and integration via REST/SOAP APIs; working knowledge of Java/J2EE, HTML, XML, SQL, and.NET for integration and legacy system touchpoints
• Hands-on proficiency with AI-assisted development tooling, including: Agentforce and Salesforce's native AI capabilities (Einstein Copilot/Agentforce agents, prompt builder, model builder) to design and deploy AI-driven workflows for business users
• AI coding assistants (e.g., Claude Code, GitHub Copilot, Salesforce Code Genie/Agentforce for Developers, Cursor) to accelerate Apex/LWC development, generate test coverage, and support code review
• Prompt engineering practices for building reliable, governed AI agents on the platform, including grounding, guardrails, and evaluation of AI-generated outputs before production deployment
• Evaluating AI-generated code and configuration for security, governor-limit compliance, and adherence to org coding standards prior to merge
• Strong research skills, including staying current on Salesforce release notes (three major releases/year) and AI feature rollouts
• Strong knowledge of industry best practices in Salesforce development (Apex design patterns, trigger frameworks, CI/CD via tools like Copado, Gearset, or Salesforce DX/SFDX pipelines)
• Knowledge of the broader sales technology tool stack and how it integrates with Salesforce (CPQ/Incentive Comp platforms, Customer Success platforms like Gainsight, work management tools like Monday.com)
• Ability to interface competently with business analysts, admins, and other technical personnel to finalize requirements and translate them into technical designs
• Ability to work well with internal teams and external SI/ISV partners
• Knowledge of test-driven development, including Apex unit testing, LWC Jest testing, and AI-assisted test generation
• Ability to write and review detailed technical specifications for complex system components, including AI agent/automation design documents
• Ability to complete complex bug fixes across Apex, LWC, integrations, and declarative automation (Flow)
• Good oral and written communication skills, including the ability to explain AI-assisted design decisions and tradeoffs to non-technical stakeholders.