Job Description

The Senior AI Engineer designs and operates production AI systems integrated with core platforms including agent workflows retrieval strategies and MLOps pipelines. This role owns end to end system design with responsibility extending from single services to integrated production-grade workflows. The AI Engineer 3 emphasizes ownership of reliability observability CI/CD practices and lifecycle management with expectations to select shape and evolve architectural and operational patterns for AI systems.

Responsibilities

• Design multi-step agent/tool workflows with clear control flow (planning vs execution separation).
• Select and implement retrieval strategies appropriate to the domain: hybrid retrieval (BM25 + vectors) multi-hop retrieval and catching.
• Implement safe rollout patterns: feature flags canaries phased traffic shifting and automated rollback triggers.
• Deliver production AI systems are integrated with core platforms (CRM/ECM) using high-availability patterns and graceful degradation.
• Define and enforce service-level objectives: latency budgets error budgets and cost budgets.
• Apply threat modeling to agent workflows and retrieval pipelines identifying risks such as prompt injection data exfiltration and context poisoning.
• Ensure secure handling of sensitive data in retrieval pipelines including PII filtering access-scoped context and audit-ready logging.
• Design human-in-the-loop escalation policies including confidence thresholds fallback routing and feedback loops.
• Own model lifecycle and operational fitness including drift detection and retraining triggers.
• Mentor coach train and provide feedback to other team members; may provide feedback to leadership on technical abilities of team.
• Build CI/CD pipelines for AI systems including data checks evaluation gates and release validation.
• Ensure model pipelines are reproducible and auditable.
• Lead architecture reviews and integration planning.
• Create reusable components such as ingestion adapters prompt libraries and observability templates.

Basic Qualifications

• Bachelor's degree or equivalent experience
• 5+ years engineering with demonstrated ownership of distributed services and production operations
• Strong CI/CD and infrastructure-as-code experience
• Experience in regulated domains involving audit trails, data lineage, and explainability artifacts
• Ships end-to-end AI systems that are reliable, measurable, and integrated with core platforms
• Improves organizational quality by making AI components reusable and governable
• Strong knowledge of systems administration and Microsoft Operating systems and products
• Microsoft Office and Excel proficient
• Strong communication, collaboration, and interpersonal skills
• Self-motivated, organized, and able to manage projects independently with minimal oversight
• Attention to detail and ability to handle sensitive information with discretion
• Ability to coach and mentor team members
• Up to 5% travel required