Software Engineer (Member of Technical Staff) – Legal Risk and Compliance

Salesforce•Dallas, TX

24d

About The Position

The Digital Enterprise Technology – Legal Risk and Compliance (LRC) Application Development team is seeking a talented and experienced Force.com Developer to design, develop, test, and enhance internal technology solutions on the Salesforce platform that support mission-critical business processes.

Requirements

4+ years of experience in Information Technology and Software Engineering.
2+ years of hands-on experience with Force.com, Apex, Lightning, and Visualforce development.
2+ years of experience in Java, JavaScript, and HTML.
Strong understanding of SOQL, SOSL, and core Salesforce products (Sales Cloud, Service Cloud, Force.com).
Experience developing test strategies, executing tests, and maintaining test automation frameworks for large enterprise projects.
Familiarity with database concepts and data modeling.
Experience with Tableau reporting, dashboard development, and engineering/productivity analytics.
Understanding of developer productivity metrics such as cycle time, PR analytics, flow efficiency, and operational reporting.
Hands-on experience or strong interest in Agentforce, AI-driven SDLC frameworks, and AI-assisted engineering workflows within the Salesforce ecosystem.
Experience integrating AI tools (Claude Code, GitHub Copilot, Codex, Cursor, etc.) into day-to-day software engineering workflows.
A demonstrated AI-first approach to engineering—using AI to accelerate development, improve quality, and enhance productivity across the stack.
Advanced prompt engineering skills and the ability to create structured prompts and system context that enable reliable, secure, and production-ready AI outputs.

Nice To Haves

Salesforce Admin and/or Developer Certification.
Experience working in an Agile development environment.
Strong understanding of the Software Development Life Cycle (SDLC).
Experience with Test-driven Development (TDD) and Continuous Integration (CI) processes.
Understanding of Software-as-a-Service (SaaS) principles.
Familiarity with Agentforce architecture, AI agents, workflow orchestration, and enterprise AI adoption patterns.
Experience building AI-enabled developer productivity dashboards and operational analytics solutions.
Strong analytical and problem-solving skills.
Ability to work independently, take ownership of projects, and manage multiple priorities in a fast-paced environment.

Responsibilities

Design, develop, test, and deploy scalable applications on the Salesforce platform (Sales Cloud, Service Cloud, and Force.com).
Write efficient, maintainable, and reusable Apex, Lightning, and Visualforce code.
Integrate quality engineering best practices, including automated testing, code quality enforcement, and environment management using Git, Jenkins, SFDX, and Salesforce CLI.
Participate in all phases of the development lifecycle—from technical design through implementation, testing, and deployment.
Collaborate with business stakeholders, technical teams, and cross-functional partners to design and implement solutions that meet business requirements.
Provide expertise on Salesforce APIs, profiles, security models, and sandbox management.
Document best practices and handoff materials for IT Support.
Contribute ideas and feedback across multiple projects within the team’s portfolio.
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of the development workflow.
Push the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining shared system context repositories, enabling AI systems to operate accurately and reliably.
Critically evaluate both human- and AI-generated code for correctness, quality, security, and performance.
Develop and maintain Tableau dashboards and engineering productivity reports to provide actionable insights into delivery performance, cycle time, and operational efficiency.
Support Agentforce implementations and AI-driven SDLC initiatives for Salesforce engineering teams, including AI-assisted development workflows, intelligent automation, and developer productivity optimization.