ESaaS - SFDC - Agentforce Dev

Highly skilled Salesforce Agentforce Specialist to lead the design,
implementation, and governance of our autonomous AI agents. In this role, you will transform
our customer service, sales, and operations by building intelligent agents that do not just chat,
but actively execute tasks and workflows.
You will bridge the gap between business requirements and technical AI
orchestration-leveraging Data Cloud, building precise prompts, and designing multi-agent
environments while adhering to strict trust and security standards.

At Zensar, we're "experience-led everything". We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we're a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

Technical Requirements
Experience: 4+ years of hands-on Salesforce ecosystem experience
(Admin/Developer/Consultant), with at least 1 year of dedicated experience building
AI-driven CRM architectures (Agentforce or Einstein Copilot).
Salesforce Core: Strong understanding of standard automation tools (Flows, Apex,
Lightning Web Components) to support custom Agent actions.
Data Literacy: Solid grasp of Salesforce Data Cloud, data modeling, ingestion, and
vector search strategies.
AI Core Concepts: Deep familiarity with prompt engineering guardrails, LLM reasoning
logic, and token optimization.
Preferred Certifications
Salesforce Certified Agentforce Specialist (AI-201) (Highly Preferred/Mandatory)
Salesforce Certified AI Associate
Salesforce Certified Platform App Builder or Platform Developer I (PD1)
Salesforce Certified Data Cloud Consultant
Soft Skills
Excellent communication skills with the ability to translate complex AI behavior into clear
business logic for stakeholders.
A strong analytical mindset to look through reasoning traces and continually tune AI
responses

Key Responsibilities
1. Agent Design & Orchestration
Configure AI Agents: Design and deploy autonomous agents using Agent Studio
utilizing Topics, Instructions, and Actions (TIA) to handle complex business
scenarios.
Action & Workflow Integration: Build and connect standard and custom agent actions
by integrating Salesforce Flows, Apex actions, and external APIs.
Multi-Agent Interoperability: Architect agent-to-agent communication protocols and
utilize the Model Context Protocol (MCP) and Agent APIs for cross-platform workflows.
2. Prompt Engineering & Grounding
Prompt Architecture: Author, manage, and optimize scalable prompt templates in
Prompt Builder using field generation and flex types.
Data Grounding: Implement robust grounding techniques using structured and
unstructured business data to prevent AI hallucinations and ensure highly relevant agent
responses.
3. Data Strategy & Data Cloud
Data Library Management: Leverage the Agentforce Data Library to feed real-time
context to the reasoning engine.
Retrieval Optimization: Configure Data Cloud retrievers, data chunking, and indexing
strategy across keyword, vector, and hybrid search methods.
4. Testing, Lifecycle & Security
Validation: Use the Agentforce Testing Center and reasoning traces to evaluate,
debug, and optimize agent decision intelligence and accuracy before live deployment.
ALM & Deployment: Manage the application lifecycle of AI models, deploying
configurations seamlessly from Sandboxes to Production environments.
AI Governance: Enforce the Einstein Trust Layer, configure Agent Users secure
access permissions, and ensure strict compliance with corporate data security and
ethical AI practices