Role overview

As a Senior Software Engineer in AI Operations at Scale AI, you will be responsible for the technical stability, performance, and long-term health of artificial intelligence solutions deployed with strategic public sector partners in Doha. While delivery teams focus on building and launching new use cases, you will serve as the technical steward ensuring these systems operate with excellence in production environments. Your work will bridge software engineering, machine learning operations, and client governance across multiple service tiers and deployment scenarios.

Key responsibilities

Conduct comprehensive technical reviews during the formal transition from development to maintenance phases, ensuring code quality, documentation standards, and architectural maintainability meet organizational requirements before approval.
Own technical response and resolution across multi-tier service level agreements ranging from business-hours support to around-the-clock mission-critical coverage, including incident governance and root cause analysis.
Monitor production model performance, system latency, and data drift patterns while managing configuration repositories to ensure behavioral consistency and performing regression testing when underlying AI provider endpoints are updated.
Evaluate incoming client requests to distinguish between routine maintenance tasks and system evolution efforts, conducting comparative assessments of new AI models against current deployments.
Design and implement automated solutions that eliminate repetitive operational work, including self-healing data pipelines, automated retrieval-augmented generation indexing, and telemetry systems that simplify ongoing maintenance.
Serve as the primary technical contact for government and enterprise IT stakeholders, translating complex AI concepts such as data drift and prompt versioning into business-relevant language for non-technical decision-makers.

Requirements

Minimum five years of professional experience in software engineering, machine learning operations, site reliability engineering, or forward-deployed roles within data-intensive or production AI environments.
Advanced proficiency in Python and SQL, with practical experience building and consuming REST and gRPC APIs within cloud platforms such as AWS, Azure, or Google Cloud Platform.
Hands-on knowledge of machine learning operations tooling, vector databases, and large language model orchestration frameworks including LangChain and LlamaIndex.
Practical understanding of prompt version control systems, model evaluation against benchmark datasets, retrieval-augmented generation pipeline architecture, and data drift detection methodologies.
Strong engineering discipline with preference for building systematic, scalable solutions over temporary fixes, including solid familiarity with continuous integration and continuous deployment practices for machine learning workflows.
Excellent technical communication abilities with the capacity to manage client expectations, establish and defend operational boundaries between maintenance and evolution work, and provide guidance on long-term system direction.

What makes this role worth considering

This position offers the opportunity to work on mission-critical AI deployments serving strategic public sector partners, combining the technical depth of machine learning operations with high-impact governance responsibilities. You will bridge the gap between cutting-edge AI development and production reliability, directly influencing how governments and enterprises deploy AI for important decisions.