- Company Name
- Intent HQ
- Job Title
- AI Orchestration Architect
- Job Description
-
**Job Title**
AI Orchestration Architect
**Role Summary**
Design, implement, and maintain end‑to‑end AI agent networks, workflows, and prompt frameworks that translate ambiguous business goals into reliable, safe, and scalable AI solutions. Act as the single point of ownership for agent interaction protocols, governance, and performance monitoring across the organization.
**Expectations**
- Scale AI‑driven automation while upholding safety, transparency, and business alignment.
- Translate human requirements into high‑integrity AI instructions and reusable prompt templates.
- Ensure agent‑to‑agent and agent‑to‑human interactions are predictable, auditable, and bias‑mitigated.
- Provide continuous monitoring, evaluation, and optimisation of system health and performance.
**Key Responsibilities**
- **Agent Network & Workflow Orchestration**
- Design, configure, and maintain multi‑agent networks (roles, capabilities, scopes, handoff logic).
- Define end‑to‑end integration of prompts, tools, agents, and humans.
- Implement modular, reusable agent components across workflows.
- **Interaction Protocols & Governance**
- Establish communication patterns, delegation logic, and escalation paths.
- Create guardrails, validation steps, and safety mechanisms for all interactions.
- Document protocols, decision logic, and system diagrams; maintain audit trails.
- **Prompt & Agent Framework Management**
- Build and maintain centralised libraries for prompts and agents.
- Develop versioning, testing, and evaluation pipelines for continuous improvement.
- Ensure adherence to quality, safety, and performance standards.
- **Prompt Engineering & Instruction Architecture**
- Design sophisticated prompt chains for multi‑step and multi‑agent workflows.
- Translate business requirements into structured, high‑reliability AI instructions.
- Create reusable templates, macros, and system messages.
- **Monitoring, Evaluation & System Health**
- Monitor real‑time agent behavior, workflow execution, and cross‑agent dependencies.
- Detect and respond to emergent behaviours; intervene when deviations occur.
- Track health metrics, failure modes, and optimisation opportunities.
**Required Skills**
- Multi‑agent system architecture and orchestration.
- Prompt engineering, instruction design, and template creation.
- Workflow design and process modelling (e.g., BPMN, flowcharts).
- Safety engineering, bias mitigation, and governance in AI.
- Version control, CI/CD for AI models and prompts.
- Monitoring dashboards, A/B testing, and performance analytics.
- Strong documentation and stakeholder communication.
- Problem‑solving and iterative optimisation mindset.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field (Master’s or PhD preferred).
- Relevant AI/ML certifications (e.g., AWS Certified Machine Learning – Specialty, GCP Professional ML Engineer, Azure AI Engineer Associate) are a plus.
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