Padmi
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Jade Global

Oracle consulting · SAP implementation

Salesforce Agentforce Developer

MumbaiPosted 7 days ago
Software engineeringUnspecifiedFull Time
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Salesforce Agentforce Developer1 AI & MODERN TOOLING EXPERTISE Candidates must demonstrate hands-on proficiency with next-generation AI tools, LLM platforms, and Salesforce AI capabilities:

CORE AI PLATFORMS & LLMS Claude (Anthropic) OpenAI Codex GitHub Copilot Cursor IDE Gemini Code Assist Amazon Q Developer

SALESFORCE AI & AGENTFORCE LAYER Agentforce Agent Builder Einstein Copilot Prompt Builder Einstein GPT MCP (Model Context Protocol) Einstein Prediction Builder

DEVELOPER PRODUCTIVITY & DEVOPS Salesforce CLI / SFDX VS Code + SF Extensions Git / GitHub Copado / Gearset Jest / Apex Test Framework Postman / REST APIs

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 Apex, SOQL, SOSL — Advanced

Lightning Web Components (LWC)

Salesforce Flow & Automation (Advanced)

REST/SOAP APIs, Named Credentials

Salesforce Data Cloud integration

Agentforce Agent Builder

Einstein Prompt Builder

Model Context Protocol (MCP)

Git, SFDX CLI, Copado / Gearset

Jest (LWC) & Apex Test Framework

Cursor IDE / AI-assisted coding

Claude API / OpenAI API integration

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 AI-curious, continuous learning mindset

Strong written and verbal communication

Bridges functional and technical conversations

Collaborative in cross-functional Agile teams

Proactively suggests AI-native process alternatives

Comfortable demoing solutions to business stakeholders

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