Sr. Salesforce DevOps Engineer
Listed on 2026-09-24
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Software Development
DevOps, AI Engineer (Applied/Software), Salesforce Developer
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.
Elastic is looking for a Sr. Salesforce Engineer & Dev Ops Specialist who combines deep architectural intuition, clean coding, and sharp debugging skills with an AI-native workflow (Cursor, Claude Code, Codex). You will serve as the technical backbone of our Salesforce ecosystem—owning the release lifecycle, managing Git Hub administration, git automation, and CI/CD pipelines, while facilitating engineering practices across Certinia PSA, CPQ/ARM, AI initiatives, and cross-functional enterprise projects.
Balancing hands‑on platform development with release engineering, you will streamline revenue processes and scale architecture to deliver high-quality, reliable production solutions.
- Dev Ops & Release Engineering:
Lead end-to-end Dev Ops operations, including Git Hub administration, git automation, branching strategies, CI/CD pipeline optimization, scratch org/sandbox management, backup strategies, and release governance. - Full-Stack Salesforce Development:
Design and build full-stack features—UI, APIs, business logic, data models, and integrations—using LWC, Apex, SOQL/SOSL, Flows, and modern REST/event‑driven patterns. - Core Business Platforms:
Drive technical design and development across Certinia PSA, CPQ/ARM, and cross-functional enterprise initiatives. - AI-Native Engineering:
Utilize AI tools (Cursor, Claude Code, Codex, Git Hub Copilot) throughout the SDLC while maintaining strict oversight, code quality, and security on AI outputs. - Quality & Deployment Control:
Establish robust deployment gates and build telemetry to monitor pipeline efficiency and release health.
- Experience:
5+ years of full-stack software engineering experience across frontend, backend, APIs, and data modeling. - Salesforce & Dev Ops Depth:
Proven expertise in Salesforce platform development alongside deep experience managing Git workflows, advanced git automation, branching strategies, Git Hub Actions, and CI/CD pipelines for enterprise deployments. - AI Tooling:
Daily proficiency using AI-assisted coding tools to accelerate scaffolding, refactoring, and debugging. - Architecture & Delivery:
Solid knowledge of software design patterns, SDLC, sandbox lifecycle management, and metadata deployment mechanics. - Education:
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
- Specialized Tools:
Hands‑on experience with native Salesforce Dev Ops platforms (Copado, Gearset) - Domain Expertise:
Practical experience developing or administering Certinia PSA, Salesforce CPQ, and/or Revenue Cloud (ARM). - Certifications:
Salesforce Development Lifecycle and Deployment Architect. Also required are Platform Developer I, Platform Developer II, Platform Administrator I, Platform Administrator II, Platform App Builder, Copado, and Certinia PSA Administrator. - Mindset:
An AI-native, adaptable engineer who thrives on solving complex architectural puzzles and elevating team engineering standards.
Compensation for this role is in the form of base salary. This role does not have a variable compensation component.
The typical starting salary…
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