$110,000–$130,000 Per Year
Amazon Web Services (AWS), Artificial Intelligence (AI), Automation, Best Practices, Cloud Architecture, Coding Standards, Customer Support/Service, Data Modeling, ERP (Enterprise Resource Planning), Microservices, Microsoft Windows Azure, Performance Tuning/Optimization, Salesforce.com, System Integration (SI), Team Player, Use Cases
Salesforce Principle Engineer with AI Experience
Must Have Technical/Functional Skills
- Proven experience as a Principal Engineer / Architect level role.
- Expertise in:
Apex, LWC, SOQL, Salesforce security model
Integration frameworks and middleware (e.g., MuleSoft)
- Hands-on experience with:
Salesforce Einstein / AI Cloud
AI/ML frameworks or API integrations
- Strong understanding of cloud architecture and microservices.
Roles & Responsibilities
- Define and own the Salesforce enterprise architecture strategy across Sales Cloud, Service Cloud,
Experience Cloud, and Marketing Cloud.
- Lead end-to-end solution design, ensuring scalability, security, and performance.
- Act as a technical advisor to stakeholders, architects, and engineering teams.
- Establish best practices, coding standards, and governance frameworks.
- Design and implement solutions using:
Apex, Lightning Web Components (LWC), Aura
Salesforce APIs (REST/SOAP)
Platform Events, Flows, and Integration patterns
- Lead complex system integrations with external platforms (ERP, data lakes, AI services).
- Optimize Salesforce performance and data models.
- Integrate AI capabilities into Salesforce using:
Salesforce Einstein (Prediction Builder, GPT, Copilot, AI Cloud)
External AI tools (Azure OpenAI, AWS AI, Google AI, etc.)
- Design use cases such as:
Predictive lead scoring and opportunity insights
Intelligent customer service automation
Chatbots and conversational AI
Recommendation engines
- Work with data teams to enable ML pipelines and data enrichment.
Salary Range- $110,000-$130,000 a year
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Tata Consultancy Services Ltd