Packaged/SaaS Application Engineer
Project Role Description : Configure and support packaged or SaaS applications to adapt features, manage releases, and ensure system stability. Use standard tools, APIs, and low-code platforms to align solutions with business needs while preserving compatibility and performance.
Must have skills : Agentforce
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Salesforce AI Core Engineer, you will operate as a hands-on junior architect, supporting the definition and implementation of AI core patterns, frameworks, and services consumed across Salesforce and other enterprise platforms. You will contribute to solution architecture, lead complex components, and help establish AI engineering best practices while remaining deeply hands-on with Salesforce and cloud AI technologies.
The role is ideal for professionals on an architect or CTA track, with strong interest in Generative AI, RAG, and multi-cloud AI services.
Roles & Responsibilities:
Support architects in designing core AI services, orchestration layers, and evaluation frameworks that can be reused across multiple applications and domains.
Lead design and development of complex AI-enabled components, including microservices, APIs, and integration layers.
Implement LLM-based features (chatbots, assistants, summarizers, recommendation engines) using cloud AI platforms and open-source frameworks.
Design and implement RAG pipelines using structured and unstructured data from Salesforce and external systems.
Develop Salesforce integration points for AI services including Apex services, invocable actions, Flows, and LWCs.
Leverage AI-assisted development tools (Copado AI, GitHub Copilot, Cursor, Claude, Agentforce Vibes, etc.) to improve productivity, code quality, and test coverage.
Participate in technical design reviews, propose improvements, and ensure adherence to standards, including performance, security, and maintainability.
Build proofs of concept (POCs) to validate AI core capabilities and demonstrate value to stakeholders.
Collaborate with business analysts, functional teams, QA, and DevOps to ensure reliable end-to-end delivery of AI features.
Contribute to internal documentation, runbooks, and knowledge-sharing sessions on AI core patterns and tools
Professional & Technical Skills:
Must Have Skills
Strong hands-on experience in Salesforce Technical Architecture.
Excellent technical skills with hands-on experience in:
o Apex
o Triggers
o Lightning Web Components (LWC)
o Salesforce Flows
o Integrations (REST/SOAP, platform events, external services)
Solid understanding of Generative AI and LLM fundamentals, including prompt engineering and hallucination mitigation.
Exposure to AI/ML services on at least one major cloud provider (Azure, AWS, or Google Cloud).
Experience using AI-powered engineering tools within enterprise development workflows.
Ability to contribute to architecture discussions, evaluate trade-offs, and recommend technical options.
Strong analytical, communication, and collaboration skills.
Strong understanding of Salesforce design patterns and development best practices.
Good to Have Skills
Experience with semantic search, embeddings, and vector stores.
Familiarity with AI guardrails (moderation, PII protection, policy enforcement).
Understanding DevOps pipelines and release governance (e.g., Copado, GitHub Actions, Azure DevOps).
Certifications Required
Salesforce Platform Developer I – Mandatory
Salesforce Platform Developer II – Mandatory
Salesforce AI Associate – Mandatory
Salesforce Agentforce Specialist – Desirable
Salesforce System Architect or Application Architect
(In-progress or completed) – Mandatory
One or more AI/Cloud certifications (Azure, AWS, Google) – Preferred.
Additional Information:
8–10 years of overall Salesforce experience.
Exposure to enterprise-scale Salesforce implementations.
Experience working in Agile / Scrum delivery models.
15 years of full-time education is required.
Bengaluru
平等就业机会声明
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