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
BEHAVIOURAL COMPETENCIES
Visionary
Designs architectures robust today and extensible for rapidly evolving AI
Governance-Minded
Rigorous on safety, trust, and regulatory compliance in AI design
Leadership
Drives consensus and mentors teams to raise Agentforce capability
Strategic
Anchors every architecture decision to measurable business outcomes
Communicator
Translates complex AI architecture into clear executive narratives
Pay: ₹100,000.00 - ₹120,000.00 per month
Experience:
- salesforce : 8 years (Required)
- architecture: 3 years (Required)
- RAG grounding: 5 years (Required)
- CI/CD: 6 years (Required)
Work Location: Remote
