Experience: 8+
Key Skills Required:
- Multi-agent orchestration — Atlas Orchestration Layer, supervisor agent design
- Salesforce Data Cloud at enterprise scale — RAG grounding, vector store, embedding pipelines
- Einstein Trust Layer, Model Builder & BYOLLM strategy
- Salesforce Prompt Builder — enterprise grounding strategy & prompt versioning
- MuleSoft, REST APIs, Platform Events for agent action integration
- CI/CD pipelines — Copado / Gearset / GitHub Actions
- AI Governance — GDPR, EU AI Act alignment, responsible AI practices
- Agent KPI architecture — containment, escalation, CSAT, latency monitoring
REQUIREMENTS
- 8+ years of Salesforce platform experience; minimum 3 years in an architecture or senior technical lead capacity
- Proven enterprise-scale Agentforce or Einstein Copilot architecture and delivery experience
- Deep expertise in Salesforce Data Cloud — identity resolution, unified profiles, RAG grounding, and data actions at scale
- Strong understanding of multi-agent orchestration patterns, Atlas Orchestration Layer, and supervisor agent design
- Experience designing enterprise integration architecture: REST APIs, Platform Events, MuleSoft, and external LLM connectivity
- Track record of defining AI governance frameworks covering trust, safety, compliance, and responsible AI practices
KEY RESPONSIBILITIES
- Define and own the enterprise Agentforce architecture: agent topology, action frameworks, trust governance, and orchestration design
- Architect Salesforce Data Cloud as the AI grounding layer: identity resolution, unified profiles, and real-time data actions
- Design multi-agent orchestration using Atlas Orchestration Layer: supervisor agents, task delegation chains, and handoff protocols
- Lead RAG architecture: vector store strategy, embedding pipelines, semantic search, and context window optimisation
- Establish enterprise Agentforce governance: topic versioning, prompt template management, guardrail policies, and Trust Layer
- Define AI safety and compliance architecture: data masking, zero-data retention, audit logging, and GDPR/AI Act alignment
- Architect Agentforce integrations with enterprise systems via REST APIs, Platform Events, and MuleSoft
- Lead BYOLLM and Model Builder strategy; evaluate Einstein Reasoning Engine for adoption roadmap
- Define agent KPI frameworks: containment rate, escalation rate, accuracy, latency, and task completion
- Provide technical governance across delivery streams; conduct design reviews and mentor Agentforce Consultants
TECHNICAL SKILLS & AGENTFORCE TOOLS
- Agentforce Agent Studio + Atlas Orchestration Layer — multi-agent topology and supervisor agent design
- Salesforce Data Cloud at enterprise scale — RAG grounding architecture, vector store, embedding pipelines
- Einstein Trust Layer, Model Builder, BYOLLM — enterprise AI governance and LLM integration design
- Salesforce Prompt Builder — prompt versioning, enterprise grounding strategy, performance evaluation
- Apex, LWC, Salesforce DX, CI/CD pipelines (Copado / Gearset / GitHub Actions) for Agentforce DevOps
- MuleSoft, REST APIs, Platform Events for agent action integration architecture
- AI compliance: GDPR, EU AI Act alignment, audit trail design, and responsible AI governance
- Agent KPI architecture: containment, escalation, CSAT, accuracy, and latency monitoring
Pay: ₹1,000,000.00 - ₹2,500,000.00 per year
Work Location: Remote
