Technical Lead (Agentforce Revenue Cloud)

UKG; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

UKG is seeking a Lead Salesforce Developer to design and deliver complex Salesforce solutions augmented with AI capabilities. You will lead technical projects while ensuring scalable and reliable solutions across the platform.

Ideal candidates have over 8 years of Salesforce development experience, including expertise in AI integration and a proven ability to mentor teams. This role is critical to shaping AI-enabled architectures within the enterprise.

Qualifications

• 8+ years of hands-on Salesforce development experience.
• Experience with Salesforce Sales Cloud, CPQ, Billing, or Revenue Cloud.
• Advanced expertise in Apex and Lightning Web Components (LWC).
• Hands-on experience integrating AI solutions in production.

Responsibilities

• Lead Salesforce development and architecture projects.
• Design and deliver AI-powered features integrated into Salesforce.
• Mentor developers and conduct technical reviews.
• Ensure platform health, performance and governance.

Skills

Salesforce development

AI solution integration

Technical leadership

API-driven architectures

Job description

Role Summary

As a Lead Salesforce Developer, you will lead the design and delivery of complex Salesforce solutions augmented with real-world AI capabilities. This role requires hands‑on experience building, integrating, and operationalizing AI‑driven functionality across enterprise platforms, not limited to Salesforce‑native AI features (for example, Agentforce, Einstein). You will shape both platform strategy and AI‑enabled architecture, ensuring solutions are scalable, governable, and production‑ready.

Key Responsibilities

Salesforce Development & Architecture

• Design, develop, and deploy complex Salesforce solutions using Apex, Lightning Web Components (LWC), Flow, and declarative capabilities.
• Drive decisions on Salesforce OOTB vs. custom solutions, with a strong bias toward scalable, maintainable architectures.
• Partner with architects and product leaders on mid‑ and high‑level solution design.

AI‑Enabled Solution Design & Integration

• Design and deliver AI‑powered features and workflows integrated into Salesforce solutions (e.g., intelligent automation, decision support, enrichment, copilots).
• Build and integrate non‑Salesforce‑native AI solutions, including:
  • LLM‑based services (for example, OpenAI, Azure OpenAI, MS CoPilot or equivalent enterprise platforms).
  • Retrieval‑Augmented Generation (RAG) patterns.
  • Tool/function calling and workflow orchestration.
• Integrate AI services with Salesforce and downstream systems via APIs, platform events, or middleware.
• Ensure AI solutions are production‑grade, with appropriate controls for:
  • Accuracy and reliability.
  • Security and access control.
  • Observability, logging, and error handling.
• Translate ambiguous business problems into practical AI‑enabled technical designs, not demos or proofs‑of‑concept.

Technical Leadership & Mentorship

• Lead and mentor developers across Salesforce and adjacent technologies.
• Conduct technical and architectural reviews, including AI design patterns and integration strategies.
• Define and evolve engineering standards, reusable patterns, and reference implementations.

Platform Health, Quality & Governance

• Own service health, reliability, and performance across Salesforce and connected AI services.
• Lead root cause analysis and remediation for platform or AI‑related incidents.
• Ensure AI usage aligns with enterprise governance, data privacy, and security expectations.

Required Qualifications

• 8+ years of hands‑on Salesforce development experience.
• Experience with Salesforce Sales Cloud, CPQ, Billing, Revenue Cloud, or Quote‑to‑Cash platforms.
• Advanced expertise in Apex, Lightning Web Components (LWC), Flow, and the Salesforce data model.
• Proven experience leading complex, enterprise‑scale Salesforce implementations.
• Hands‑on experience building and integrating AI solutions in production environments, beyond packaged Salesforce AI features.
• Strong understanding of API‑driven architectures, system integrations, and enterprise security models.

Preferred Qualifications

• Experience with LLM‑based application patterns (prompt engineering, RAG, agent/tool orchestration).
• Experience integrating Salesforce with AI platforms such as Azure OpenAI, OpenAI APIs, or equivalent enterprise‑grade AI services.
• Familiarity with AI evaluation, monitoring, or guardrail patterns (accuracy, determinism, regression).
• Salesforce Platform Developer II and/or relevant AI/cloud certifications.