Senior Salesforce Engineer

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is the Role? Elastic is looking for a Sr. Salesforce Engineer who combines deep architectural intuition, clean coding, and sharp debugging skills with an AI-native workflow using tools like Cursor, Claude Code, or Codex across the entire stack. Adaptable and deeply curious, you will dive into platforms like Salesforce and MuleSoft while holding an end-to-end ownership mindset to elevate engineering practices and turn ambiguous business challenges into high-quality, reliable production solutions. In this role, success goes beyond ticket counts; you will streamline critical revenue processes, scale platform architecture, and leverage AI to build smart automations that eliminate manual work, serving as a key technical partner driving meaningful business impact. What You Will 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., Agent Builder, 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. What You Bring • 5+ years of professional full-stack software engineering experience — strong fundamentals across frontend, backend, APIs, and data. • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline. • 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. Bonus Points • 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 . Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $94,300—$149,200 USD The typical starting salary rang