Senior AI Engineer
New
I
InfiterraSubscription commerce
Greece (Remote); UK (Remote). This is a fully remote senior individual-contributor role based in either Greece or the UK.Full-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Fluent English, written and spoken.
- Required Skills
- PythonCI/CDRESTful APIsDistributed Systems
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 or fine-tuning where appropriate.
- Ability to select an AI approach based on problem context and evaluation evidence.
- Experience designing behavioural, groundedness and business-correctness, robustness, and regression evaluations.
- Experience with production evaluation, monitoring, and feedback loops.
- Strong software-engineering background, particularly in 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.
- Ability to address reliability, testability, latency, and cost, and investigate complex failures.
- Ability to understand complex workflows, business rules, dependencies, and constraints and translate ambiguous 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.
Responsibilities
- Own the design, implementation, evaluation, and production operation of complex AI systems involving multiple components, integrations, or workflows.
- Translate ambiguous business problems, rules, and domain constraints into measurable AI and system behaviour.
- Select AI approaches based on evidence, including prompting, retrieval, orchestration, predictive ML, and model adaptation or fine-tuning where justified.
- Build production systems using model APIs, structured outputs, retrieval/RAG, agentic and tool-based workflows, and other appropriate AI patterns.
- Design evaluations for functional behaviour, groundedness, business correctness, robustness, and regressions.
- Establish production monitoring and feedback loops using evaluation evidence, logs, metrics, traces, and operational data.
- Engineer systems for reliability, testability, observability, maintainability, latency, and cost.
- Diagnose complex AI and software failures and turn production learning into prevention and system improvement.
- Identify and validate AI-enabled improvements to SDLC, product, and operational workflows.
- Work with Architecture, Platform, Security, Data, Quality, Product, and domain specialists; mentor less-experienced engineers and contribute reusable practices.
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