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Scale AI is seeking a Senior Software Engineer for AI Operations to own the technical health, performance, and stability of AI solutions deployed across strategic public sector partners. This role bridges software engineering, MLOps, and client governance in a production-focused environment.
Key responsibilities include:
• Handover & Onboarding: Act as technical gatekeeper during transitions from Delivery to Maintenance, conducting deep-dive reviews to ensure code, prompts, and architecture meet strict maintainability standards.
• SLA & Incident Management: Own technical response and resolution across multi-tiered service models (Business-Hours Essential to 24/7 Mission-Critical). Lead incident governance, root cause analysis, and P1/P2 mitigations within active support windows.
• AI Lifecycle Governance: Monitor production model performance, latency, and data drift. Manage prompt configuration repositories, maintain behavioral consistency, and perform regression testing when LLM providers update endpoints.
• Request Classification: Operationalize boundaries between Routine Maintenance (in-scope) and System Evolution (out-of-scope). Assess client requests and benchmark new AI models.
• Automation & Reliability: Engineer self-healing data pipelines, automated RAG indexing syncs, and telemetry tooling. Influence upstream teams to adopt maintainable architectural patterns.
• Client Technical Interface: Serve as senior technical point of contact for government and enterprise IT leads, translating AI concepts into clear business impacts.
Ideal candidates have 5+ years in Software Engineering, MLOps, SRE, or Forward Deployed Engineering in production AI environments. Required: advanced Python, SQL, REST/gRPC APIs, cloud architecture (AWS/Azure/GCP), MLOps tooling, vector databases, and LLM orchestration frameworks. Desired: prompt version control, model benchmarking, RAG pipeline mechanics, data drift detection, CI/CD for ML pipelines, and strong client communication skills.
