Principal Software Engineer Salesforce AI

Equinix

5 - 10 years

30 - 32 Lacs

bengaluru

Posted:1 week ago| Platform:

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Skills Required

salesforce lightning apex salesforce sales force development data privacy visualforce metadata soql salesforce platform searching sfdc enterprise architecture dbms triggers artificial intelligence sales javascript marketing lwc

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Summary

As a Salesforce AI Architect, you will lead the design and implementation of AI capabilities within the Salesforce ecosystem, focusing on intelligent agent frameworks (Agentforce), custom model integrations, and retrieval-augmented generation (RAG).
This role is central to evolving our Salesforce platform into a more autonomous, context-aware environment that supports scalable, secure, and governed AI solutions.
You will partner closely with the architects, engineers, OCTO, the Salesforce Governance Lead, and data science teams to ensure alignment with enterprise architecture and responsible AI practices and drive innovation across GTM processes, sales intelligence, and customer engagement in support of our Lead-to-Cash Vision: Make it easy for sellers to win and for leaders to coach and influence the outcome.

Responsibilities

Architect and implement AI capabilities within Salesforce, including autonomous agents, orchestration layers, and intelligent workflows using Agentforce principles
Design and deploy Retrieval-Augmented Generation (RAG) pipelines that connect Salesforce with external content sources (e.g., enterprise knowledge bases, vector databases, private LLMs).
Lead the integration of custom and private AI models into Salesforce, ensuring secure, performant, and governed interactions across business processes
Collaborate with Salesforce Platform teams to embed AI into declarative and programmatic components (e.g., Flows, Apex, LWC)
Build scalable AI services interacting with Salesforce data and metadata, enabling intelligent decision-making and automation
Partner with data science and ML engineering teams to operationalize models within Salesforce workflows
Work closely with Salesforce Platform Architect, Cross-Domain Architects, OCTO, and Governance Leads to align AI architecture with enterprise standards and ethical guidelines
Partner with Cross-Domain Architects and Product Owners to translate business needs into AI-enabled Salesforce solutions
Support product teams in identifying opportunities for AI augmentation across Lead-to-Cash and customer lifecycle processes
Define and enforce best practices for AI model integration, prompt engineering, data privacy, and performance optimization within Salesforce
Contribute to improving governance frameworks for AI usage in Salesforce, including model lifecycle management, auditability, and responsible AI principles
Stay current with Salesforce AI innovations (e.g., Einstein GPT, Prompt Builder, Copilot Studio) and broader industry trends
Create prototypes and proofs of concept to refine and define requirements. Design solutions that facilitate data flow and communication between disparate systems
Support the development of new lead-to-cash processes from Account to Opportunity and the implementation of spoke systems tied to lead-to-cash across Sales, Marketing, and Channels (e.g., SFDC Account Engagement, Clari, Anaplan, Zoominfo, etc.)
Suggest best code practices for Salesforce/other Lead-to-Cash application capabilities, making key decisions on custom solutions as necessary and translating them to a high-performance technical solution

Qualifications

Must Have

BS in Computer Science, Engineering, Machine Learning, or related field
5+ years of experience in Salesforce development or architecture, with at least 2 years focused on AI/ML integration within enterprise platforms
Salesforce Certified Agentforce Specialist
Strong understanding of Salesforce AI capabilities, including Einstein GPT, Prompt Builder, and Copilot Studio
Hands-on experience with LLM integration into Salesforce workflows, including custom/private model orchestration
Familiarity with Agentforce principles and autonomous agent design within Salesforce or similar platforms
Strong communication skills with the ability to translate complex AI concepts into business-friendly language
Proficiency in Apex, Lightning Web Components (LWC), and Salesforce APIs for building and integrating intelligent solutions
Ability to collaborate with Salesforce Platform Architects, Cross-Domain Architects, OCTO, and Governance Leads to align AI architecture with enterprise standards
Strong understanding of data privacy, security, and governance considerations in AI model deployment

Nice to Have

MS in Computer Science, Engineering, Machine Learning, or related field
Salesforce Certified Data Cloud Consultant
Knowledge of Salesforce metadata architecture and how it can be leveraged for AI-driven automation
Experience implementing Retrieval-Augmented Generation (RAG) pipelines using external content sources (e.g., enterprise knowledge bases, vector databases)
Experience contributing to AI governance frameworks, including model lifecycle management and ethical AI practices
Background in prompt engineering, vector search, or semantic retrieval techniques
Ability to multitask, working on more than one assignment simultaneously
Flexibility to support in other time zones, if required

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