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Leading Digital Solutions - for good.
AI Engineer – Human-Led AI Orchestration, Action Points
Location
United States
Posted
7 days ago
Salary
0
Seniority
Senior
Job Description
AI Engineer – Human-Led AI Orchestration, Action Points
Servant
- Design and implement AI-driven workflows that generate actionable, human-directed insights. - Build and optimize LLM-powered systems for summarization, recommendation, classification, and orchestration. - Implement agentic AI patterns that operate under explicit human guardrails and approval flows. - Translate unstructured data into structured Action Points™ aligned with user goals. - Develop and maintain prompt architectures and evaluation frameworks for consistent AI output quality. - Architect and develop semi-autonomous AI agents with mandatory human-in-the-loop control points, safety guardrails, and review checkpoints. Voice to Text - Design and implement AI-driven voice workflows that generate actionable, human-directed insights. - Architect real-time speech-to-text pipelines for AI control, command execution, and Action Point generation. - Implement low-latency voice ingestion using Azure Speech SDK for real-time transcription, intent detection, and multilingual support. - Ensure voice inputs are securely processed, auditable, and aligned with human authorization and approval flows. - Translate spoken input into structured, human-directed Action Point that govern downstream AI agents. Integration & Deployment - Deploy AI services using FastAPI and integrate them securely with backend systems. - Collaborate with frontend and backend engineers to expose AI capabilities via secure APIs. - Ensure AI systems scale reliably in cloud environments (Azure-based). Performance, Ethics & Governance - Optimize inference latency, throughput, and cost efficiency. - Implement observability, logging, and monitoring for AI workflows. - Apply responsible AI principles: transparency, auditability, and human override by design.
Job Requirements
- Strong experience in Python with AI/ML systems.
- Hands-on experience with LLMs (OpenAI API or similar).
- Experience deploying AI services with FastAPI.
- Familiarity with agentic AI frameworks and orchestration patterns.
- Experience working in cloud-based AI environments (Azure preferred).
- Solid understanding of data processing, evaluation, and optimization.
- Proficiency with Git and collaborative development workflows.
- Preferred Qualifications
- Experience with vector databases (e.g., PGVector).
- Familiarity with MLOps practices and AI CI/CD pipelines.
- Experience with prompt engineering and evaluation frameworks.
- Exposure to multi-tenant SaaS AI systems.
Benefits
- Flexible Hours & Compensation**
- Our client offers a flexible work structure of **20–40 hours per week**, depending on role scope and workload. This role is outcome-driven, not hour-tracked.
- Compensation is provided as a **fixed monthly stipend**, aligned to responsibilities and expected ownership. The stipend remains consistent as long as commitments are met and performance remains strong.
- This environment requires:
- Clear ownership and follow-through
- Proactive communication
- Consistent, high-quality delivery
- Flexibility is paired with accountability—team members are trusted to manage their time while ensuring outcomes, team continuity, and customer commitments are fully upheld.
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