The Programmer Analyst is the builder-orchestrator; the person who turns solution designs into working, production-quality software, increasingly by specifying, directing, and rigorously verifying AI-generated code, not only by hand-writing every line. You will write Apex, build Lightning Web Components, design Flows, implement integrations, and deliver the features and enhancements that power Illumina’s Commercial and Services organizations on the Salesforce platform, working fluently with AI coding assistants while remaining fully accountable for the correctness, security, and quality of everything you ship.

You are responsible for the majority of hands-on delivery on the team, increasingly by directing and verifying AI-generated code, not only writing it by hand. You will work from solution designs provided by Solution Architects, under technical direction set by the Technical Architect, and in close collaboration with Test Automation Engineers who validate your work. You will produce clean, well-tested, secure code that meets Illumina’s engineering standards and scales to support a global organization, whether you typed it or an AI agent produced it, you own it.

This role operates within an Agile Scrum delivery model. You will participate in sprint planning and grooming alongside Product Owners, Solution Architects, Technical Architects, and TAEs. You will collaborate with TAEs to define test strategy for your features; quality is a shared responsibility, built into every sprint, not a handoff at the end. As the Salesforce platform evolves with AI capabilities like Agentforce and Data Cloud (Data 360), you will build and implement these solutions alongside the rest of the engineering team. As AI takes on more first-pass implementation, your leverage shifts upstream, to clear specifications, strong tests, and disciplined review, and your judgment about what “good” looks like becomes the most valuable thing you bring.

Software Development

• Write production-quality Apex code; classes, triggers, batch processes, queueable jobs, and scheduled Apex. Follow the team’s architectural patterns (trigger handler frameworks, service/domain/selector layers) and coding standards defined by the Technical Architect.
• Build Lightning Web Components (LWC); custom UI components using HTML, CSS, and JavaScript within the LWC framework. Implement wire services, imperative Apex calls, event handling, and Lightning Message Service. Follow SLDS design patterns and accessibility standards.
• Design and build Flows; record-triggered, screen, scheduled, and autolaunched flows. Make appropriate decisions about when to use declarative automation vs. Apex based on the team’s established guidelines.
• Implement integrations; REST/SOAP API callouts, Platform Events, Change Data Capture, and named credentials. Build error handling, retry logic, and logging into integration implementations. Work with middleware where required.
• Implement Agentforce solutions; build custom Apex actions for agents, configure Prompt Builder templates, write Agent Script for deterministic control, and implement Trust Layer guardrails as directed by solution designs.
• Implement Data Cloud (Data 360) configurations; data streams, data model objects, identity resolution, calculated insights, and activations based on solution designs and architectural direction.
• Configure Salesforce platform features; objects, fields, validation rules, page layouts, permission sets, sharing rules, and other declarative elements as part of feature delivery.

AI-Augmented Engineering

• Work in agentic, spec-driven workflows: write a clear specification and acceptance criteria, delegate first-pass implementation to AI coding assistants, then review, correct, test, and own the result.
• Engineer the context AI tools need to be useful and safe: maintain rules/standards files, ground agents in the org’s metadata via the Salesforce DX MCP, and supply relevant examples and data.
• Verify AI-generated code with the same rigor as peer code, checking intent, security (CRUD/FLS, SOQL injection), governor-limit safety, hallucinated APIs, and adherence to team patterns. Treat verification as first-class engineering.
• Use AI coding assistants (such as Cursor and Agentforce Vibes, plus conversational tools like Claude or ChatGPT Enterprise where approved) to accelerate development, refactoring, debugging, test writing, and documentation, and share effective prompts and patterns with the team.
• Follow Illumina’s rules for safe use of AI tools on regulated health data: respect data boundaries, never expose PHI/PII or secrets, and understand the IP and authorship implications of AI-generated code.

Code Quality & Testing

• Write comprehensive unit tests for all Apex code; positive, negative, and bulk scenarios. Achieve meaningful test coverage beyond the 75% minimum. Use test data factories and proper mocking techniques.
• Participate in code reviews; both as a reviewer and as a contributor receiving feedback. Provide constructive, educative feedback to peers. Address code review feedback promptly and thoughtfully.
• Follow the team’s coding standards, security practices, and architectural patterns. Write code that is clean, maintainable, well-documented, and aligned with the Technical Architect’s direction.
• Write secure code; enforce CRUD/FLS checks, prevent SOQL injection, protect against XSS/CSRF, and implement appropriate data access controls. Follow the team’s secure coding guidelines.
• Collaborate with Test Automation Engineers to define test strategy for your features during sprint planning. Ensure your implementations are testable and that acceptance criteria are met before handoff.
• Identify and reduce technical debt in the areas you work in. Refactor legacy code when opportunities arise during feature delivery. Advocate for technical improvements during sprint planning.
• Verify AI-generated code as rigorously as hand-written code; ensure unit tests meaningfully cover AI-produced implementations, where subtle logic errors and hallucinated APIs tend to hide.

DevOps & Deployment

• Use Git (GitHub) for version control; branching, committing, creating pull requests, and resolving merge conflicts. Follow the team’s branching strategy and PR workflows.
• Deploy code and metadata using the team’s CI/CD pipeline (AutoRabit, DevOps Center, Salesforce CLI). Troubleshoot deployment failures and resolve metadata conflicts.
• Manage sandbox environments for development and testing. Maintain environment hygiene and coordinate with TAEs on test data and environment needs.
• Support release activities; pre-deployment validation, smoke testing, and post-deployment verification. Participate in release planning by identifying dependencies and risks.

Collaboration & Delivery

• Participate actively in Agile Scrum ceremonies; sprint planning, daily standups, backlog grooming, sprint reviews, and retrospectives.
• Collaborate with Solution Architects to understand solution designs and ask clarifying questions before implementation begins. Raise concerns about feasibility, complexity, or alternative approaches early.
• Work under the technical direction of the Technical Architect; following established patterns, participating in design discussions, and seeking guidance on complex implementation decisions.
• Collaborate with Test Automation Engineers throughout the sprint; not just at handoff. Share early builds, discuss test scenarios, and work together to ensure features are delivered with quality.
• Communicate progress, blockers, and risks proactively. Escalate technical challenges early rather than struggling in isolation.
• Support production issues; troubleshoot, diagnose, and fix defects in production. Participate in incident response and post-incident reviews. Learn from production issues to improve future implementations.

Growth & Continuous Learning

• Invest in continuous learning; new Salesforce platform features, Agentforce capabilities, Data Cloud, and evolving development practices. Use Trailhead, documentation, and self-directed learning to stay current.
• Leverage AI coding assistants (such as Cursor, Agentforce Vibes, Claude, ChatGPT Enterprise, or similar) to accelerate development. Critically evaluate AI-generated code for correctness, security, and adherence to team standards.
• Share knowledge with the team; through documentation, brown bags, code review discussions, and mentoring less experienced engineers.
• Pursue relevant Salesforce certifications to deepen platform expertise and validate skills.

Experience

• 5+ years of hands-on Salesforce development experience (Apex, LWC, Flows, and/or platform configuration).

• Experience writing Apex code; classes, triggers, unit tests, and SOQL/SOSL queries. Understanding of governor limits and bulkification patterns.
• Experience building Lightning Web Components or equivalent modern JavaScript-based UI components.
• Experience with Salesforce declarative automation; Flows, validation rules, and platform configuration.
• Experience with version control (Git) and CI/CD practices for Salesforce deployments.
• Experience working in Agile Scrum delivery models.
• Experience with Salesforce integrations (REST APIs, Platform Events) is preferred.
• Experience with ServiceMax, Conga CPQ/CLM, Data Cloud, or Agentforce is a plus.
• Experience with regulated environments (HIPAA, FDA, SOX) is preferred.
• Certifications (Preferred): Foundation & Platform - Salesforce Administrator, Platform App Builder.
• Certifications (Preferred): Development & Specialization - Platform Developer I, Platform Developer II, Agentforce Specialist, Data Cloud (Data 360) Consultant.

Knowledge, Skills & Abilities

Technical

• Proficiency in Apex development; object-oriented programming, trigger patterns, SOQL/SOSL queries, DML operations, governor limits, and bulkification.
• Proficiency in Lightning Web Components; HTML, CSS, JavaScript, wire services, imperative Apex, event handling, and SLDS.
• Understanding of Salesforce declarative automation; Flows (record-triggered, screen, autolaunched), validation rules, and the order of execution.
• Understanding of the Salesforce data model, security model (profiles, permission sets, sharing rules, FLS), and multi-tenant architecture constraints.
• Working knowledge of Salesforce integration patterns; REST/SOAP APIs, Platform Events, Change Data Capture, and named credentials.
• Familiarity with DevOps tooling; Git/GitHub, AutoRabit or Salesforce CLI for deployments, and CI/CD pipeline concepts.
• Awareness of Agentforce and Data Cloud (Data 360) concepts; willingness to learn and implement these evolving platform capabilities.
• Understanding of secure coding practices; CRUD/FLS checks, SOQL injection prevention, and XSS/CSRF protection.
• Fluency with AI-augmented engineering: agentic and spec-driven workflows, context and prompt engineering (rules files, Salesforce DX MCP, grounding), and critical verification of AI-generated code, using assistants such as Cursor, Agentforce Vibes, Claude, or ChatGPT Enterprise.

Professional

• Builder mindset; takes pride in writing clean, well-tested, maintainable code. Cares about craft, not just getting it done.
• Collaborative; works effectively with SAs, TAs, TAEs, POs, and fellow engineers. Treats quality as a shared responsibility. Assumes positive intent.
• Communicative; articulates progress, blockers, and technical tradeoffs clearly. Asks questions rather than making assumptions. Documents work for the team’s benefit.
• Growth-oriented; invests in learning new platform capabilities, accepts feedback constructively, and actively seeks to improve. Uses AI tools to accelerate development while maintaining critical evaluation.
• Accountable; delivers on commitments. Takes ownership of their work quality. Transparent about challenges and timelines.
• Detail-oriented; thorough in implementation and testing. Considers edge cases, error handling, and downstream impacts.

• Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or equivalent related work experience.