Job Description

Salesforce Agentforce Developer1

AI & MODERN TOOLING EXPERTISE

Candidates must demonstrate hands-on proficiency with next-generation AI tools, LLM platforms, and Salesforce AI capabilities:

SALESFORCE CLOUD EXPERTISE (Any of 2 clouds as mentioned below)

Sales Cloud

Deep expertise in Lead-to-Opportunity lifecycle, Territory Management, Forecasting, and Activity Timelines. Build AI-assisted rep coaching nudges and pipeline automations using Agentforce Sales Agents and Next Best Action.

Service Cloud

Proficiency in Case Management, Entitlements, SLA enforcement, Omni-Channel routing, and Knowledge Base management. Deploy Agentforce Service Agents for intelligent case deflection, auto-resolution, and escalation management.

Experience Cloud

Build partner portals, patient portals, and B2B communities using LWR sites. Integrate Einstein personalisation, AI-powered search, and audience segmentation for contextual digital experiences.

Revenue Cloud (CPQ & Billing)

Configure and extend CPQ product catalogues, pricing waterfalls, bundle rules, discount schedules, and approval chains. Automate quote generation and contract amendments using AI Prompt Templates and Agentforce.

Health Cloud

Develop on Care Plans, Patient 360 timeline, Referral Management, and the FHIR Interoperability Hub. Implement AI-assisted care gap identification and proactive patient outreach automations.

Data Cloud & Marketing Cloud

Build Data Cloud calculated insights and activation flows that feed personalised journeys in Marketing Cloud. Understand how unified customer profiles power AI segmentation and Einstein-driven content recommendations.

INDUSTRY DOMAIN KNOWLEDGE (Any one of following)

Healthcare & Life Sciences

• Understanding of Patient Lifecycle: acquisition, care coordination, treatment, discharge, and follow-up automation

• HIPAA compliance, PHI handling, field-level encryption, and consent management within Salesforce

• HL7/FHIR R4 standards and Salesforce Health Cloud Interoperability Hub integration patterns with EHR systems

• Prior Authorization, referral management, care plan automation, and population health workflow awareness

• Value-based care models and how AI can drive outcomes tracking and proactive care gap closure

Hi-Tech & Software

• SaaS business models: ARR, MRR, NRR, churn, expansion revenue, and renewal lifecycle awareness

• Lead-to-cash process knowledge: SDR workflows, AE handoffs, CSM playbooks, and renewal automation

• Partner ecosystems: deal registration, co-sell motions, reseller pricing tiers, and MDF management

• Product-Led Growth (PLG) integration: product usage telemetry triggering Salesforce actions via MCP/API

• Software entitlement management, license tracking, and usage-based billing awareness

FUNCTIONAL KNOWLEDGE (FOUNDATION FOR AI SOLUTIONS)

Deep functional knowledge enables professionals to design AI-powered Salesforce solutions that reflect real business intent — not just technical requirements. This is what separates good implementations from transformative ones.

Sales Process Understanding

A developer who understands the full sales funnel — from lead generation and qualification through negotiation to closed-won — can build smarter Agentforce Sales Agents, more meaningful pipeline automations, and AI scoring models grounded in real selling behaviour, without requiring constant BA intervention.

Customer Service Operations

Knowing how service teams triage, escalate, and resolve cases across channels enables developers to design intelligent routing rules, AI deflection agents with real resolution paths, and SLA-aware automations that genuinely reduce average handle time and improve CSAT.

Revenue & Quoting Cycles

Understanding how products are configured, priced, discounted, and contracted allows developers to engineer dynamic CPQ rules, AI-assisted quote recommendations, and approval chains that Finance and Sales Ops teams will actually trust in production.

Healthcare Workflow Literacy

Developers aware of care coordination workflows, patient consent flows, clinical documentation cycles, and referral processes can embed Agentforce agents meaningfully into Health Cloud environments — designing for real clinical scenarios, not just demo happy paths.

KEY RESPONSIBILITIES

• Design, develop, and deploy scalable Apex classes, triggers, batch jobs, queueables, and Lightning Web Components across multi-cloud Salesforce implementations

• Build and configure Agentforce Agents (Service, Sales, and Custom) with domain-relevant topics, actions, and instructions grounded in real business workflow knowledge

• Integrate external AI models and enterprise data sources into Salesforce via Model Context Protocol (MCP) servers and Platform APIs

• Develop Einstein Prompt Templates, Prompt Builder flows, and Einstein Copilot Actions to deliver contextual AI assistance within Salesforce records and processes

• Use Cursor, Claude, or GitHub Copilot daily to accelerate code generation, unit test writing, documentation, and peer code review

• Build integrations with EHR systems, SaaS platforms, ERP systems, and data warehouses using REST/SOAP APIs, Platform Events, and Change Data Capture

• Implement CI/CD pipelines using Copado or Gearset with automated Apex and LWC test suites, achieving minimum 85% code coverage

• Collaborate with BAs and Architects to understand functional requirements and translate them into well-documented technical designs

• Ensure code quality, platform security (CRUD/FLS), and compliance (HIPAA, SOC 2) across all deliverables

AI & AGENTFORCE SPECIFIC RESPONSIBILITIES

• Design Agentforce Agent Topics, Actions, and Instructions aligned to domain-specific use cases: patient intake, sales coaching, case resolution, renewal outreach

• Implement MCP (Model Context Protocol) servers to expose Salesforce objects, Apex actions, and APIs as structured context for Claude, GPT-4o, or other LLMs

• Build Prompt Builder templates and Einstein Copilot Skill integrations that deliver AI-native experiences directly within Salesforce records and action panels

• Use Cursor IDE with Salesforce extensions for AI-pair-programmed Apex, LWC, and integration development — reducing boilerplate effort by 40–60%

• Generate unit tests, data factory classes, and technical specification documents using Claude or Codex as a development accelerator

• Prototype and validate AI-agent workflows in Salesforce sandbox using Agentforce canvas before hardening for production deployment

• Monitor Agentforce agent performance via Analytics dashboards and iterate on agent instructions based on resolution rate and escalation metrics

TECHNICAL SKILLS & QUALIFICATIONS

NICE TO HAVE

• Salesforce Certified AI Specialist or AI Associate credential

• FHIR R4 API experience with Salesforce Health Cloud Interoperability Hub

• Hands-on Salesforce Data Cloud: data streams, identity resolution, calculated insights

• MuleSoft or Boomi enterprise integration patterns

• Python or Node.js for LLM orchestration alongside Salesforce (LangChain, CrewAI)

• Open-source contributions or active Salesforce Trailhead / community presence

SOFT SKILLS & MINDSET