Software Engineering & DevOps AI Rater/Evaluator
LILT AI
About the role
Overview LILT is building a global network of domain experts to support high‑quality AI evaluation across training, benchmarking, red‑teaming, and ongoing model monitoring. We are seeking software engineering and DevOps professionals to contribute expert judgment to human‑in‑the‑loop AI evaluation workflows used by leading enterprises and hyperscalers. This role is designed for professionals who understand how software systems, infrastructure, and development practices work in real production environments and who can apply that expertise to evaluate, assess, and improve multilingual AI systems. Your contribution of expertise will directly influence multilingual AI model quality, safety, and deployment readiness. Track A: Software Engineering & DevOps AI Rater Raters execute structured evaluation tasks using clearly defined rubrics and instructions. Responsibilities • Evaluate AI outputs related to software engineering, DevOps, and infrastructure topics • Perform structured scoring, comparison, classification, and judgment tasks • Assess technical correctness, completeness, security implications, and best‑practice alignment • Identify hallucinations, incorrect code, unsafe recommendations, or misleading system guidance • Apply domain‑specific engineering and DevOps guidelines consistently across tasks Ideal Background • Software engineers, site reliability engineers, DevOps engineers, or platform engineers • Experience with production systems, CI/CD pipelines, cloud infrastructure, or distributed systems • Strong attention to detail and comfort working with structured evaluation criteria Track B: Software Engineering & DevOps AI Evaluator (Senior Track) Evaluators provide higher‑level technical oversight and help shape how evaluation is performed. Responsibilities • Validate and refine evaluation rubrics and edge‑case handling • Perform adjudication where raters disagree • Conduct error analysis and qualitative reviews of model behavior • Partner with LILT research, product, and customer teams on evaluation design • Support red‑teaming, security review, and model readiness assessments Ideal Background • Senior software engineers, DevOps leads, SREs, or technical architects • Experience defining technical standards, reviewing complex edge cases, or advising on system design and reliability • Ability to clearly explain nuanced technical reasoning and tradeoffs Evaluation Focus & Requirements Types of AI Evaluation Work based on project demands: • Software engineering and infrastructure content evaluation • Code correctness and reasoning assessment • DevOps, CI/CD, and cloud architecture evaluation • Security and reliability‑focused red‑teaming • Ongoing model monitoring and regression testing What We Look For • Deep domain expertise in software engineering, DevOps, or infrastructure • Strong technical judgment and ability to apply criteria consistently • Comfort working with structured evaluation workflows • Ability to explain reasoning clearly, especially in complex or high‑risk technical scenarios • Reliability, professionalism, and respect for quality standards Engagement Model • Contract‑based, flexible participation • Project‑based work with clear expectations and timelines • Opportunities for recurring work based on performance and demand • Compensation communicated upfront per project or task type Why This Work Matters • Provide accurate and safe technical guidance • Align with real‑world engineering and DevOps best practices • Are reliable, secure, and trustworthy across languages Language Requirements • Native or professional fluency in one or more supported languages is required • Supported languages span 30+ global languages • Language‑specific nuance is assessed through screening and task‑based evaluation, not separate job descriptions • English fluency is required for guidelines, feedback, and collaboration LILT\'s mission is to make the world\'s information available to everyone, no matter the language they speak. Join our global community who thrive on innovation and excellence. Our collective knowledge, uniqueness, and skills deliver multilingual AI and human‑verified services to Enterprises, Governments, and AI Developers around the world. Earn money. Have fun. Advance human knowledge. Work on diverse projects from anywhere, any time you want. Get paid quickly and fairly, and build your professional network in a supportive community—all through a streamlined application process tailored to your expertise. Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT\'s Privacy Policy at LILT is committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision‑making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt‑out of the use of AI in our hiring process, please let us know at LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.
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Salary: EUR 45000 - 65000 per year
Requirements
- deep domain expertise in software engineering, DevOps, or infrastructure
- strong technical judgment and ability to apply criteria consistently
- comfort working with structured evaluation workflows
- ability to explain reasoning clearly, especially in complex or high-risk technical scenarios
- reliability, professionalism, and respect for quality standards
Responsibilities
- evaluate AI outputs related to software engineering, DevOps, and infrastructure topics
- perform structured scoring, comparison, classification, and judgment tasks
- assess technical correctness, completeness, security implications, and best-practice alignment
- identify hallucinations, incorrect code, unsafe recommendations, or misleading system guidance
- apply domain-specific engineering and DevOps guidelines consistently across tasks
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