Glean AI Engineer
- Canada
Contract
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Job details
- Job type
- Contract
- Posting language
- English
- Posted
Original job description
Project Description:
We are placing senior AI engineers to design and deliver production agentic AI systems for an enterprise client. You will build autonomous agents on the client’s existing enterprise AI stack.
Glean is the agent platform and OpenAI / GPT Enterprise provides the reasoning layer, deployed on AWS or GCP.
This is hands-on build work. You own agents from design through production, monitoring, and iteration.
You approach agents as production software.
You work in terms of triggers, retrieval, reasoning steps, actions, permissions, evaluation, and observability, and you know how to make an agent reliable, secure, and maintainable at enterprise scale.
Responsibilities:
We are placing senior AI engineers to design and deliver production agentic AI systems for an enterprise client. You will build autonomous agents on the client’s existing enterprise AI stack.
Glean is the agent platform and OpenAI / GPT Enterprise provides the reasoning layer, deployed on AWS or GCP.
This is hands-on build work. You own agents from design through production, monitoring, and iteration.
You approach agents as production software. You work in terms of triggers, retrieval, reasoning steps, actions, permissions, evaluation, and observability, and you know how to make an agent reliable, secure, and maintainable at enterprise scale.
Requirements:
Must-Have Experience Agentic AI and LLMs
- 3+ years building with LLMs in production systems that real users depend on.
- Hands-on experience designing agentic workflows: tool and function calling, retrieval-augmented generation (RAG), multi-step orchestration, and memory.
- OpenAI / GPT Enterprise.
- Deep practical experience with the OpenAI API and GPT Enterprise: model selection, prompt engineering, structured outputs, function calling, cost and latency tuning, and data-handling controls.
- Strong prompt-engineering discipline and an evaluation-first approach. You measure agent quality with evals rather than by inspection.
Glean
- Glean is required. Direct, hands-on production experience with the Glean platform: Agent Builder, Apps, Actions, Model Hub, connectors, and permission-aware retrieval.
- This is a non-negotiable requirement for the role.
- Working knowledge of enterprise search and RAG architecture on Glean: indexing, connectors, retrieval quality, and runtime permission enforcement.
- We need an AI platform admins with experience with API, MCP, integrations/user permissions experience.
More about this job
Responsibilities
Design, build, and deploy autonomous AI agents on the client’s Glean and OpenAI/GPT Enterprise stack, hosted on AWS or GCP. Own agents through production, monitoring, evaluation, and iteration, ensuring they are reliable, secure, and maintainable at enterprise scale.
Requirements
Requires at least three years of production LLM experience, hands-on agentic workflow design, and deep practical experience with the OpenAI API and GPT Enterprise. Direct production experience with Glean - including Agent Builder, Apps, Actions, Model Hub, connectors, and permission-aware retrieval - is mandatory, along with experience in APIs, MCP, integrations, and user permissions.
Skills
- Agentic AI
- Large Language Models
- OpenAI API
- GPT Enterprise
- Glean
- Prompt Engineering
- Retrieval-Augmented Generation
- Tool and Function Calling
- Multi-Step Orchestration
- Enterprise Search
- Evaluation and Evals
- API Integrations
- Model Context Protocol
- User Permissions
- Cloud Platforms
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
Keywords
- Agentic AI
- Large Language Models
- OpenAI API
- GPT Enterprise
- Glean
- Agent Builder
- Glean Apps
- Glean Actions
- Model Hub
- Connectors
- Retrieval-Augmented Generation
- Enterprise Search
- Permission-Aware Retrieval
- Tool Calling
- Function Calling
- Multi-Step Orchestration
- Memory
- Prompt Engineering
- Structured Outputs
- Evaluation
- Observability
- API Integrations
- Model Context Protocol
- User Permissions
- AWS
- Google Cloud Platform
- Cost Optimization
- Latency Optimization
- Data-Handling Controls