Senior AI Engineer

Job not on LinkedIn

🔥 3 minutes ago

🌐 Greece, United Kingdom – Remote

🇬🇷 Greece – Remote 🇬🇧 United Kingdom – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Infiterra

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Infiterra is a subscription commerce platform that helps IT distributors, managed service providers (MSPs), and telcos automate quote-to-bill operations and run cloud marketplaces. The company provides a unified SaaS solution for product catalog management, cloud marketplace storefronts, subscription billing, credit-risk controls, reseller management, vendor integrations, payment and back-office connectors, and open APIs to streamline provisioning, billing, and reporting. Infiterra positions itself as a B2B partner that accelerates time-to-market, reduces operational friction, and scales multi-vendor cloud businesses through automation and enterprise-grade security.

📋 Description

• Design, build, evaluate and operate production AI systems solving product and engineering problems • Own complex AI systems end-to-end, from ambiguous business problem discovery through experimentation, implementation, deployment, monitoring and continuous improvement • Work on AI-native product engineering and knowledge systems • Develop automated and reusable vendor-integration capabilities and evolve the Integration Hub • Enable AI-assisted software delivery across analysis, requirements, implementation, testing, knowledge reuse, code review and delivery acceleration • Build AI-enabled quality and production intelligence capabilities, including anomaly detection, failure-pattern analysis, data-quality/error detection and intelligent monitoring • Select AI approaches based on evidence, including prompting, retrieval, orchestration, predictive ML, model adaptation/fine-tuning and specialized models • Build production systems using model APIs, structured outputs, retrieval/RAG, agentic and tool-based workflows and predictive techniques • Design evaluations covering functional behaviour, groundedness, business correctness, robustness and regressions • Establish monitoring and feedback loops using evaluation evidence, logs, metrics, traces and operational data • Engineer for reliability, testability, observability, maintainability, latency and cost • Diagnose complex AI and software failures and convert production learning into prevention and system improvement • Identify and validate AI-enabled improvements to SDLC, Product and operational workflows • Collaborate with Architecture, Platform, Security, Data, Quality, Product and domain specialists while retaining technical accountability • Mentor less-experienced engineers and contribute reusable patterns, knowledge and practices

🎯 Requirements

• Strong hands-on experience delivering production AI systems • Experience with model APIs, structured outputs, tool-based systems, retrieval/RAG, agentic workflows, predictive techniques and model adaptation/fine-tuning where appropriate • Ability to select the appropriate AI approach based on problem context and evaluation evidence • Experience designing behavioural, groundedness/business-correctness, robustness and regression evaluations, including production evaluation, monitoring and feedback loops • Strong software-engineering background, particularly Python • Experience with distributed systems, APIs, integrations, data pipelines, automated testing, CI/CD, containers/cloud and production-grade engineering practices • Strong observability and production troubleshooting skills, including logs, metrics and traces • Reliability, testability, latency/cost awareness and complex failure investigation skills • Ability to understand complex workflows, business rules, dependencies and constraints and translate ambiguous business problems into reliable system behaviour • Demonstrated ability to take complex technical problems from discovery and experimentation through production and continuous improvement • Fluent English, written and spoken • Experience with MCP or equivalent tool/context interoperability patterns (desirable) • Experience with orchestration technologies such as LangGraph, Temporal or equivalent (desirable) • Experience with model adaptation/fine-tuning or production predictive ML (desirable) • Experience building evaluation harnesses and datasets from real production/user feedback (desirable) • Experience with unstructured data and knowledge/retrieval systems at scale (desirable) • Working knowledge of AI security, privacy and responsible-AI practices (desirable) • Experience improving developer/product workflows through applied AI (desirable) • Experience with anomaly detection, intelligent monitoring or AI-assisted operational analysis (desirable)

🏖️ Benefits

• Work-from-anywhere scheme • Regular team get-togethers in person, with travel and accommodation covered • Flexible working hours • Health and life insurance programme • Learning & development budget • Tech-driven, friendly team with an international mindset