About the Role
AI Agent Developer | 100% Remote
Role:
Contract-to-Hire (Only GC and USC)
Duration:
12 Months+
Location:
100% Remote
Legal:
No sponsorship provided at this time.
We are seeking a seasoned
AI Agent Developer
to bridge the gap between enterprise data and actionable automation. You will be responsible for architecting and deploying sophisticated AI agents across
Glean
and
Slack
, transforming complex enterprise workflows (IT, HR, Manufacturing, Supply Chain) into seamless, conversational experiences.
This isn't just about chatbots; it's about building multi-step, reasoning-capable agents that interact with the core systems of a modern business.
An AI Agent Engineer to design, build, and deploy intelligent AI agents that automate workflows, interact with enterprise data, and support decision-making. The ideal candidate will have experience with LLMs, agent orchestration frameworks, APIs, vector databases, and data engineering.
The role involves developing AI systems capable of reasoning, tool usage, memory management, retrieval-augmented generation (RAG), and workflow automation across business applications.
Key Responsibilities:
Core Responsibilities
Design and build Glean agents utilizing conversational flows, task automation, and advanced RAG (Retrieval-Augmented Generation) patterns.
Develop robust Slack agents using the Bolt framework, Slack workflows, functions, events, and complex API integrations.
Translate departmental needs (e.g., Jira ticketing, Workday onboarding, Salesforce updates) into operational AI agents.
Create reusable agent boilerplates that support multi-step reasoning and tool-calling capabilities.
Ensure all agentic workflows adhere to strict enterprise governance, logging, and security protocols.
AI Agent Development
Design and develop autonomous and semi-autonomous AI agents
Build multi-agent systems for task orchestration
Integrate LLMs into enterprise applications
Create conversational AI and workflow agents
Implement agent memory, planning, and reasoning capabilities
Data Integration & RAG
Connect AI agents to structured and unstructured data sources
Build Retrieval-Augmented Generation (RAG) pipelines
Develop document ingestion and embedding workflows
Work with vector databases and semantic search systems
Ensure data quality, governance, and secure access
Automation & Tooling
Integrate APIs, SaaS tools, and databases
Build AI-powered workflow automation systems
Develop tool-calling and function-calling architectures
Automate business processes using AI agents
Model & Infrastructure
Fine-tune and evaluate LLM performance
Optimize prompts and inference pipelines
Deploy AI services in cloud or on-prem infrastructure
Monitor latency, reliability, and agent performance
Required Skills
Core AI/LLM Skills
Strong understanding of LLMs and generative AI
Prompt engineering and agent orchestration
RAG architecture and semantic retrieval
Function calling and tool usage
Multi-agent frameworks
Programming
Python (preferred)
JavaScript/TypeScript (optional)
API development and integration
SQL and database querying
Technical Requirements
5+ years of experience
specifically focused on building AI Agents and LLM-powered applications.
Platform Expertise:
Glean experience is highly preferred.
Strong engineering background in
Python
,
Node.js
, or
TypeScript
.
Mastery of LLM orchestration frameworks like
LangChain
,
LangGraph
, or equivalent toolsets.
Proven track record of integrating with enterprise-grade APIs:
HR/IT:
Workday, ServiceNow
CRM/Ops:
Salesforce, Jira
Supply Chain:
Custom ERP/MFG interfaces