Senior Software Engineer, AI Operations

Role Overview

Key Responsibilities

• Act as the technical gatekeeper during the transition from delivery to maintenance.
• Review code, prompts, architecture, and documentation for maintainability before handover sign-off.
• Own response and resolution targets across tiered service models, including business-hours and 24/7 support.
• Lead incident governance, root cause analysis, and P1/P2 mitigations.
• Monitor model performance, latency, and data drift in production.
• Manage prompt repositories and regression testing when LLM provider endpoints change.
• Classify client requests as routine maintenance or system evolution and benchmark new AI models.
• Engineer self-healing data pipelines, automated RAG indexing synchronization, and telemetry tooling.
• Influence delivery teams to adopt architectures that simplify ongoing maintenance.
• Serve as senior technical contact for government and enterprise IT leads.

Technical Expectations

• The role requires senior-level technical ownership of deployed AI solutions in production environments.
• The role requires expertise spanning software engineering, MLOps, AI lifecycle governance, incident management, and reliability engineering.
• The role requires clear communication of technical AI concepts and operational impacts to non-technical stakeholders.

Client Interface

• Work includes direct technical interaction with government and enterprise IT leads.