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Agent Enterprise Jobs (NOW HIRING)

Vista Equity Partners Management

$200K - $315K/yr

Lead end-to-end delivery of AI agent implementations using Vista's Agentic Factory methodology ... Design appropriate autonomy levels for enterprise agent deployments, incorporating human-in-the ...

ApplyBoard, Inc.

Agent management, compliance tracking, and training Capio works with institutions that want greater ... The Opportunity: We're looking for an Enterprise Sales Manager to help expand Capio's footprint ...

PepsiCo

AI Enterprise Platform Architect

Plano, TX · On-site

$123K - $206K/yr

Enterprise SaaS Agentic Architecture (30%) Define solution architecture patterns for Agentforce and AssistNow implementations, including how agent capabilities are designed, integrated, and governed ...

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Agent Enterprise information

What is the difference between Agent Enterprise vs Agent Developer?

AspectAgent EnterpriseAgent Developer
Required CredentialsCertifications in enterprise software, cloud platformsProgramming certifications, software development skills
Work EnvironmentLarge organizations, enterprise-level projectsSoftware development teams, tech startups
Employer & Industry UsageIT firms, corporations with complex systemsTech companies, software firms
Search & Comparison IntentUnderstanding enterprise-focused rolesComparing development roles in tech

Agent Enterprise typically involves managing and deploying enterprise-level solutions, focusing on large-scale systems and cloud integrations. Agent Developer, on the other hand, emphasizes software development, coding, and creating applications. While both roles require technical skills, Agent Enterprise is more about system management and deployment, whereas Agent Developer centers on programming and software creation.

What are some common challenges faced by Agent Enterprise professionals when managing large-scale client accounts?

Agent Enterprise professionals often encounter challenges such as balancing the diverse needs of multiple large clients, navigating complex organizational structures, and ensuring consistent delivery of high-quality service across accounts. Effective communication, strong project management skills, and adaptability are crucial for overcoming these challenges. Close collaboration with internal teams such as sales, technical support, and product development is often necessary to address client concerns and deliver tailored solutions.

What is an Agent Enterprise?

An Agent Enterprise typically refers to a company or organization that acts as an intermediary or representative on behalf of clients, handling services such as sales, customer support, or operations. These enterprises often employ agents who work to connect clients with products, services, or solutions tailored to their needs. Agent Enterprises are common in industries like real estate, insurance, travel, and telecommunications, where personalized service and client advocacy are important. Their main goal is to facilitate smooth transactions and provide value-added support to both clients and service providers.

What are the key skills and qualifications needed to thrive as an Agent Enterprise, and why are they important?

To excel as an Agent Enterprise, you need a strong background in business development, client relationship management, and a relevant degree or industry experience. Familiarity with CRM software, data analytics tools, and sales platforms is typically required. Exceptional communication, negotiation, and problem-solving skills help you build trust and deliver tailored solutions to clients. These abilities are essential for driving business growth, maintaining client satisfaction, and achieving organizational objectives.
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What job categories do people searching Agent Enterprise jobs look for? The top searched job categories for Agent Enterprise jobs are:
Agent Enterprise jobs near you
Infographic showing various Agent Enterprise job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Enterprise AI Engineer (GCP)

INFT Solutions Inc

Atlanta, GA • On-site, Remote

Contractor

Posted 16 days ago

Job description

Job Description: Enterprise AI Engineer (GCP)
Location: Remote / Hybrid Focus: Agentic AI, Data Intelligence, and Enterprise Scale
Role Overview
We are looking for a Principal Enterprise AI Engineer to architect and deliver high-impact AI
solutions within the Google Cloud ecosystem. This role is designed for a technical leader who
can bridge the gap between complex data landscapes and autonomous AI systems. You will lead
the development of Agentic AI frameworks and Data Intelligence platforms that drive
significant digital transformation for global enterprise clients.
Core Responsibilities
 Architect Agentic Systems: Design and deploy multi-agent orchestration frameworks
using Vertex AI Agent Builder, LangGraph, or CrewAI to automate complex, multi-step
business workflows.
 Master RAG Architectures: Build and optimize high-performance Retrieval-
Augmented Generation (RAG) systems, ensuring LLMs are grounded in enterprise data
across BigQuery and Databricks.
 Model Strategy & Optimization: Select and fine-tune models within the Gemini 1.5
family, balancing high-reasoning capabilities (Pro) with high-speed efficiency (Flash) for
production-grade latency.
 Legacy Transformation: Lead the strategic migration of legacy analytics logic (e.g.,
SAS environments) into modern, AI-powered cloud architectures.
 GTM Collaboration: Work closely with Go-To-Market (GTM) leadership to translate
technical AI roadmaps into measurable business value for C-suite stakeholders.
Required Skill Requirements
1. Agentic AI & Orchestration
 Framework Mastery: Expert implementation of LangChain, LangGraph, or
LlamaIndex for stateful, autonomous agent development.
 Advanced Prompting: Proficiency in Chain-of-Thought (CoT), ReAct patterns, and
system instruction optimization to ensure reliable model output.
 Function Calling: Experience building custom tools that allow LLMs to interact
securely with enterprise APIs and SQL databases.
2. Data Intelligence & Engineering
 Hybrid Data Ecosystems: Deep experience integrating Google Cloud AI services with
Databricks (Delta Lake) for unified data intelligence.
 Vector Engineering: Proficiency with Vertex AI Vector Search (formerly Matching
Engine) and embedding strategies for large-scale semantic search.
 Data Flow: Skill in building scalable pipelines using Dataflow or Spark to process
unstructured data for AI readiness.
3. LLMOps & Production Engineering
 Evaluation Frameworks: Ability to build automated "LLM-as-a-judge" evaluation
pipelines to track accuracy, faithfulness, and hallucination rates.
 Cloud Infrastructure: Mastery of the Vertex AI suite (Studio, Model Garden, Pipelines)
and Infrastructure as Code (Terraform).
 Programming: Expert-level Python (FastAPI, Pydantic) and advanced SQL.
4. Strategic Governance
 Responsible AI: Implementation of safety filters, PII redaction, and ethical AI
monitoring.
 Business Translation: Ability to convert technical metrics (latency, token costs) into
business KPIs (ROI, process efficiency).
Qualifications
 Experience: 8+ years in Software Engineering or Data Science, with at least 3+ years
focused on production-grade AI/ML.
 Education: B.S./M.S. in Computer Science, AI, or a related quantitative field.
 Certifications: Google Professional Machine Learning Engineer or Professional Cloud
Architect (preferred).
Technology Stack
 AI/ML: Vertex AI, Gemini 1.5 Pro/Flash, PyTorch.
 Data: BigQuery, Databricks, Vertex Vector Search.
 Orchestration: LangGraph, Vertex AI Agent Builder.
 DevOps: GitHub Actions, Terraform, Vertex AI Pipelines.