Software Engineer, Full Stack & AI-Native Development (MTS)
- Location
- Dallas, Texas, United States
- Track
- Full Stack AI
- Level
- Staff
- Posted
- October 30, 2026
- Source
- Workday
Job description
Job Category
Software Engineering
The Experience
The Digital Enterprise Technology – Legal, Risk & Compliance (LRC) Application Development team is looking for a sharp, curious Full Stack Software Engineer who loves building great software and building it fast with modern AI tooling. This role is first and foremost about engineering excellence: strong fundamentals, clean architecture, and the ability to ship end-to-end features across the stack.
We're looking for someone who treats AI coding assistants as a core part of the craft, not a side skill — using tools like Cursor, Claude Code, and Codex daily to move faster, explore designs, and raise code quality.
You'll work across the full stack — frontend, backend, APIs, data, and integrations — with Salesforce as the primary building platform. Salesforce experience is a plus, not a must-have — we'll get you ramped quickly if you bring strong core engineering skills.
What You'll Actually Be Doing
- Design, build, and ship full-stack features end-to-end — UI, APIs, business logic, data models, and integrations — with a strong bias for clean, maintainable, well-tested code.
- Build modern frontend experiences (component-based UI, responsive design) and robust backend services and APIs, applying solid object-oriented and software design principles.
- Use AI-assisted development tools — Cursor, Claude Code, Codex, GitHub Copilot, or similar — throughout the SDLC: scaffolding, refactoring, test generation, debugging, and code review, while maintaining engineering rigor over AI-generated output.
- Design and implement integrations using REST APIs, event-driven patterns, and enterprise integration practices.
- Where the work runs on Salesforce, develop using Lightning Web Components (LWC), Apex, SOQL/SOSL, Flows, and the platform's security model — with support to ramp up if you're new to the platform.
- Explore and build agentic and AI-powered features (e.g., Agentforce, workflow automation, AI agents) that bring real automation and intelligence into business processes, with appropriate governance and human-in-the-loop checks.
- Own features through the full lifecycle: solution design, development, testing, deployment, and production support.
- Contribute to CI/CD, automated testing, code reviews, and Agile ceremonies; and raise the bar on engineering practices across the team.
You're Our Person If...
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline.
- 4+ years of professional full-stack software engineering experience — strong fundamentals across frontend, backend, APIs, and data.
- Proficiency in modern frontend technologies (JavaScript/TypeScript, HTML, CSS, modern frameworks) and backend development (object-oriented programming, RESTful API design, databases/SQL, data modeling).
- Hands-on, daily experience using AI-assisted coding tools such as Cursor, Claude Code, Codex, GitHub Copilot, or similar — able to write precise prompts and critically evaluate AI-generated code for correctness, security, and performance.
- Solid grounding in software design patterns, SDLC, Agile methodologies, Git, and CI/CD practices.
- Strong analytical and problem-solving skills, with the ability to independently design and deliver scalable technical solutions.
- Excellent communication and cross-functional collaboration skills.
Even Better If...
- Experience developing on the Salesforce platform (Apex, Lightning Web Components, SOQL/SOSL, Salesforce Flows, platform security model) — a strong plus.
- Exposure to Agentforce, Data Cloud, Einstein AI, or other AI-agent/workflow-orchestration platforms.
- Experience with enterprise integration tools (MuleSoft, Platform Events, Named Credentials) or event-driven architectures.
- Salesforce Platform Developer I/II certification, or equivalent industry certifications.
- Familiarity with cloud platforms (AWS, Azure, or GCP), containerization, and observability/engineering productivity metrics.
- Experience shipping a production AI-powered feature (e.g., agentic workflows, RAG, LLM-backed UI) — one of the strongest signals we look for.
What Makes You Successful
- A true engineer at heart: someone who can reason about architecture, write clean code, and diagnose hard bugs — with or without AI in the loop.
- Genuinely AI-native: you reach for Cursor, Claude Code, or Codex by default, and use them to build fluency across the stack, not just in your specialty.
- Curious and adaptable — comfortable picking up new platforms (including Salesforce, Mulesoft) quickly when the work calls for it.
- Ownership mindset: you drive features to done, care about quality, and elevate the engineers around you.
- Excited about applying AI meaningfully to real business problems — automation, decision support, and smarter workflows .