AI Engineer

Virtusa

. Design, configure, and deploy multi-step AI agents using Salesforce Agentforce, including topics, actions, prompt templates, reasoning engines, and guardrails .

Posted 11/12/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying AI agents using Salesforce Agentforce and Databricks, with a strong focus on integrating enterprise APIs and ensuring compliance and security across workflows. Proficient in building backend data pipelines and optimizing agentic architectures for production environments.

Highest-signal resume keywords

Salesforce AgentforceDatabricksMachine Learning EngineeringREST APIsAgentic Architectures

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLMosaic AIGraphQLTool/Function CallingPlanning LoopsMemory ManagementHybrid RAGEvaluation FrameworksCost Optimization

Tools & Technologies

Salesforce AI EcosystemUnity CatalogModel ServingKnowledge GraphsRole-Based Access Control

Industry Keywords

Enterprise Data GovernanceAuthentication ProtocolsCompliance GuardrailsAgent InteractionsBusiness Workflows

Tech Stack

Tools & technologies

ERPGraphQLPythonSparkSQLUnity

About the role

Key responsibilities & impact

Design, configure, and deploy multi-step AI agents using Salesforce Agentforce, including topics, actions, prompt templates, reasoning engines, and guardrails
Build backend data, RAG, and tool-calling pipelines on Databricks using Mosaic AI, Vector Search, Unity Catalog, and Model Serving
Integrate enterprise APIs, knowledge graphs, and CRM/ERP data sources so agents can retrieve context and execute actions securely
Implement evaluation frameworks, latency and cost optimizations, and observability for agentic workflows in production
Enforce security, role-based access control (RBAC), and compliance guardrails across all agent interactions
Design, build, and deploy autonomous and human-in-the-loop AI agents across enterprise platforms

Requirements

What you’ll need

3+ years of software engineering, ML engineering, or applied AI experience, with hands-on delivery of LLM-based agents in production
Practical experience with Salesforce Agentforce (or Einstein Copilot / Salesforce AI ecosystem) and Databricks (Mosaic AI, Spark, Python, SQL)
Strong understanding of agentic architectures: tool/function calling, planning loops, memory management, and hybrid RAG
Solid experience with REST/GraphQL APIs, authentication protocols (e.g., OAuth, OIDC), and enterprise data governance
Ability to translate business workflows into deterministic guardrails and reliable prompt/action designs
Ability to work hours overlapping with US hours during onboarding, until 7:00 PM at the latest