AI Operations Engineer

Навыки

• ASR / TTS
• AWS
• Azure
• CI/CD
• Дашборды и витрины
• Data Governance
• Data Quality

О компании и продукте

• We are looking for a Machine Learning Operations/ Language Model Operations Engineer

Задачи

• Design and implement scalable, source-agnostic ingestion pipelines for production ML and LLM data
• Build and maintain data processing workflows including ingestion, redaction, storage, classification, and slicing of production signals
• Define and implement data storage strategies, including tiering, retention policies, and privacy-aware data handling
• Develop observability and debugging tools, including dashboards and query systems for production AI systems
• Implement evaluation and monitoring frameworks, including offline evaluation sets, online autoraters, and regression detection systems
• Build automated triage systems to identify, classify, and surface production failures
• Develop and maintain PII redaction mechanisms and enforce data governance and compliance policies at ingestion level
• Design and operate LLM evaluation mining workflows to continuously improve model and prompt performance
• Implement alerting systems to detect regressions across model and prompt deployments
• Collaborate with AI, engineering, and product teams to ensure robustness and reliability of production AI systems
• Evaluate and select tooling, infrastructure, and hosting strategies for ML/LLM platforms
• Own the operational reliability of the entire ML/LLM data and evaluation pipeline
• Job Description
• In this role, you will be responsible for designing, building, and operating the end-to-end infrastructure that supports production AI systems, ensuring reliability, observability, data quality, and continuous improvement of machine learning and LLM-based solutions

Требования

• Proven experience building and operating production-grade data platforms or ML systems, including ingestion, storage, access control, monitoring, and on-call responsibilities
• Hands-on experience developing ML/LLM evaluation systems (e.g., regression test sets, autoraters, LLM-as-a-judge frameworks, or golden datasets)
• Strong understanding of LLM observability, tracing, and debugging tools
• Experience implementing data privacy controls such as PII redaction in production environments
• Deep understanding of failure modes in ML and LLM systems (hallucinations, retrieval failures, agent loops, ASR/TTS degradation, prompt/model regressions)
• Strong production-level Python engineering skills, with a hands-on mindset
• Solid understanding of data pipelines, system reliability, and distributed data processing
• Nice-to-Have Skills
• Experience in multi-tenant or SaaS architectures with strict data isolation requirements
• Familiarity with Azure and/or AWS cloud ecosystems
• Experience making infrastructure trade-off decisions between managed services and self-hosted solutions
• Knowledge of vector databases, embedding techniques, and clustering or unsupervised failure detection methods
• Experience with data versioning tools such as LakeFS, DVC, or Delta Lake
• Familiarity with GDPR, data deletion workflows, and compliance-driven data systems
• Exposure to embedded, automotive, or constrained environments
• Experience with non-English language model evaluation or multilingual datasets
• Experience working with LLM APIs such as Anthropic Claude, OpenAI models, or open-source alternatives
• Familiarity with CI/CD workflows, GitHub-based development, and modern DevOps practices
• Experience with dashboard development using TypeScript or similar frontend technologies
• Additional Information
• At Tieto, we believe in the power of diversity, equity, and inclusion
• We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation
• Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity
• Tieto Iberia is part of the Tieto Group and combines local expertise with the global strength of Tieto, a leading software and digital engineering services company with worldwide presence and capabilities

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