Software Engineering / IT Ops SME

About this role

About Turing: Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM, and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview: We are seeking an AI Training Specialist (IT Ops & Software Management) to set domain quality benchmarks and build reference logic for technical-focused AI applications. In this role, you will convert complex software engineering workflows, ITSM frameworks, SLA policies, and asset management protocols into structured parameters and deterministic spreadsheet models. You will design, evaluate, and refine domain assets to ensure AI-generated ticket workflows, triage logic, and IT operations reports align with professional industry standards. Requirements: Core Experience: 3+ years in software engineering, IT operations, or technical support management. Domain Expertise: Hands-on familiarity with issue trackers, ITSM helpdesks, SLA policies, escalation paths, and asset lifecycle management. Logic & Technical Translation: Strong, concise professional writing with a proven ability to translate triage workflows, SLA timers, and incident rules into deterministic spreadsheet formulas and parameters. Availability & Commitment: Talent must have weekend on-call availability (part-time engagement is acceptable). Technical Infrastructure: Personal desktop/laptop equipped with a stable, high-speed internet connection in a remote setup. Responsibilities: Domain Guidance & Guardrail Authoring: Define operational discovery parameters and technical guardrails for AI tools handling IT ticketing, incident management, and software support workflows. Golden Asset Construction: Build and verify reference IT dashboards, SLA tracking sheets, asset lifecycle rollups, and triage escalation logic in Google Sheets or Excel. Workflow & Dataset Co-Design: Design realistic IT service scenarios and validate domain context files, including system incident logs, post-mortems, and support playbooks. AI Quality Audit & Sign-Off: Review, score, and refine AI-generated technical outputs to ensure complete alignment with professional software engineering and ITIL practices. Education & Experience Bachelor's degree or equivalent practical experience in any field. Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred but not required. Offer Details: Commitments Required: 40 hours per week with 8 hours of overlap with PST. Engagement type: Contractor Engagement Length: upto 2 weeks Availability: Talent must have weekend on-call availability (part-time engagement is acceptable). Evaluation Process - Shortlisted candidates will be sent a Job Interest Form . Finalized talents will go through delivery review & proceeded further accordingly.