[Hiring] Senior Software Engineer @Keysight Technologies, Inc.

Role Description

• Hunt down technical debt — dead automations, bloated triggers, redundant fields, and queries that scan half the database for one record.
• Audit and rationalize automations into a single, sane framework.
• Monitor org health proactively — governor limits, storage, API consumption, deployment stability.
• Build production-grade Apex — bulkified, governor-limit-aware, single-trigger-per-object, with proper separation of concerns.
• Develop Lightning Web Components that are reusable and accessible.
• Hold the quality bar in code reviews — meaningful test assertions, no hardcoded IDs, clean error handling, sensible naming.
• Own and improve the CI/CD pipeline — scratch orgs, source-driven development, automated test gates, and deployments.
• Design and maintain integrations via REST/SOAP APIs, Platform Events, and Change Data Capture.
• Champion data quality — deduplication strategies, validation rules, and migration practices.
• Troubleshoot sync failures and API limit issues across connected systems.
• Define and document development standards and best practices.
• Mentor junior developers through pairing, reviews, and knowledge sharing.
• Evaluate every Salesforce release for features worth adopting and deprecations worth addressing.
• Help the team make smart clicks-vs-code decisions.

Qualifications

• Deep hands-on skills in Apex, SOQL/SOSL, LWC, and enough Visualforce knowledge to maintain legacy components.
• Strong JavaScript/ES6+, HTML, and CSS fundamentals.
• Expertise in Salesforce’s security architecture — profiles, permission sets, sharing rules, FLS, OWDs, role hierarchy.
• Solid Git workflow habits — branching, pull requests, merge conflict resolution.
• Proficiency with Salesforce CLI, scratch orgs, metadata API, and at least one CI/CD tool.
• Sharp debugging instincts — Debug Logs, Query Plan tool, Limit monitoring.
• Familiarity with data migration/ETL tools — Data Loader, Dataloader.io, or equivalent.
• Comfortable in Agile/Scrum rhythms without needing a ceremony for every decision.

Requirements

• Understanding of AI/ML fundamentals — supervised vs unsupervised learning, model training, evaluation metrics, and data pipelines.
• Exposure to Large Language Models (LLMs) — prompt engineering, fine-tuning concepts, RAG, and API-based integrations.
• Familiarity with generative AI use cases in enterprise contexts — summarization, classification, content generation, conversational bots, and intelligent search.
• Experience using AI-assisted development tools for code generation, test scaffolding, or automated code review.
• Basic comfort with Python or similar languages for scripting AI/ML workflows, data wrangling, or prototyping.
• Awareness of responsible AI principles — bias, explainability, data privacy, and governance considerations.

Benefits

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 5–9 years of hands-on Salesforce platform development — cloud-agnostic, problem-first.
• Active Salesforce certifications preferred — Platform Developer I/II, Application Architect, System Architect, or any specialist certification.
• Clear communicator who can explain a complex technical tradeoff to a business stakeholder.