AI Agent Engineer, Workforce Experience
New
O
OrbisAI automation
Location: Remote-USFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- Must have 5 years of proven experience translating user requirements into wireframes, workflows and such. Must have 1-year proven experience utilizing Claude or similar commercial offering to build AI agents. Desired: 5-7 years experience in software development.
- Required Skills
- PythonRESTful APIsPrompt EngineeringLangChain
Requirements
- Have at least 5 years of proven experience translating user requirements into wireframes and workflows.
- Have at least 1 year of proven experience using Claude or a similar commercial offering to build AI agents.
- Demonstrate experience building a functioning multi-agent workflow and explaining its design rationale, agent handoffs, context sharing, failures, and fixes.
- Have practical command of prompt engineering, including retrieval-augmented generation (RAG) and tool or function calling.
- Explain technical work, system behavior, limitations, and failure modes to non-technical audiences.
- Elicit requirements from stakeholders who cannot provide a specification and reach a working solution.
- Troubleshoot agent workflows using platforms such as Claude, GPT-class models, LangChain, AutoGen, or CrewAI, and isolate failures across prompts, tools, data, and orchestration.
- Have working proficiency with APIs and scripting ability to build and debug workflows independently; JSON payloads or Python scripts must not be a blocker.
- Use sound judgment about model output and identify when it should not be trusted.
- Produce strong written documentation, runbooks, and reports for program leads and executives.
- Have experience building production internal tooling for non-engineering colleagues and designing intake or self-service that reduces manual request handling.
- Demonstrate success driving adoption through documentation, training, and enablement, and measuring whether it took hold.
Responsibilities
- Design, build, and deploy multi-agent and automated workflows for triage, data retrieval, summarization, reporting, and escalation routing.
- Translate process owners’ descriptions into workflow specifications and explain system behavior, reliability, and limitations to non-technical stakeholders.
- Partner iteratively with process owners to develop capabilities that fit their operations.
- Monitor production workflows, diagnose failures across prompts, tools, data, and orchestration, and resolve them.
- Track AI workload costs and identify efficient ways to deliver the required outcomes.
- Define accuracy standards, human review checkpoints, and escalation criteria, and build checks to verify quality.
- Maintain runbooks and SOPs, integrate workflows across Catalyst, Pulse, and Discovery, and produce recurring reports and data exports.
- Build internal tooling, intake, and self-service mechanisms for employees using agent workflows.
- Drive adoption through documentation, training, office hours, and feedback; measure usage, resolution, and employee satisfaction.
- Identify internal processes to automate and maintain the internal knowledge base.
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