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27 Π΄Π½Π΅ΠΉ Π½Π°Π·Π°Π΄

Senior AI Engineer

Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
hybrid
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
senior
Π‘Ρ‚Ρ€Π°Π½Π°
Finland
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ΠœΡΡ‚Ρ‡ & Π‘ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄

ΠŸΠΎΠΊΠ°ΠΆΠ΅Ρ‚ Π²Π°ΡˆΡƒ ΡΠΎΠ²ΠΌΠ΅ΡΡ‚ΠΈΠΌΠΎΡΡ‚ΡŒ ΠΈ Π½Π°ΠΏΠΈΡˆΠ΅Ρ‚ письмо

ОписаниС вакансии

TL;DR
Senior AI Engineer (Agentic AI/MLOps): Building and operating agentic AI tooling for the Operations team, including an internal production-issue investigation agent, with an accent on infrastructure, observability, and reliable production workflows. Focus on expanding agentic use cases, validating AI-generated output, integrating data pipelines, and preparing systems for locally hosted models and on-prem deployments.
Senior AI Engineer


ROLE HIGHLIGHTS:
* Senior AI Engineer


* Location: Espoo, Finland


* Department: Engineering


* Reports to: Engineering Lead (Operations)


* Employment type: Permanent


* Workplace model: Hybrid, 3 days a week at the office


* Employment is subject to applicable security screening (incl. SUPO)



WHY THIS ROLE MATTERS:
As a Senior AI Engineer you’ll build the agentic tooling that changes how the Operations team works.

You will make agentic AI real for the Operations team: the tooling, the workflows, and the infrastructure behind them. The starting point is an internal agent that already investigates production issues automatically and is being picked up by other domains, and from there you'll shape where agentic approaches genuinely earn their place in the team's work.

This role sits at the intersection of software engineering, DevOps, and MLOps. You will build the infrastructure this tooling needs to run reliably, partner directly with engineering teams on what to build next, and bring a grounded, forward-looking view of what agentic AI can realistically deliver, including preparing for a future move toward locally-hosted models and on-prem deployments.




WHO WE ARE
ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth.




ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system.




ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future.




Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific.




Your day-to-day responsibilities

* Own the team's internal agentic AI system, spanning issue analysis, early detection, and prevention to improve customer perceived system quality, and lead its adoption across the wider engineering organization


* Identify and prioritize where else agentic workflows can meaningfully improve how the Operations team works, beyond the current flagship agent


* Build the infrastructure, tooling, and operational discipline (AIOps, data pipelines, monitoring) the system needs to run reliably in production


* Bring a forward-looking, hands-on view of what AI agents can realistically do today and in the next 6-12 months, and apply that judgment to the agent's roadmap, including preparing for a future move toward locally-hosted models



What we’re looking for

* Versatile, hands-on software engineering background, comfortable working across different backend languages and technologies


* A track record of building and owning an agentic AI system or comparable AI-driven tool end-to-end, not just using one


* Solid DevOps foundation: infrastructure, deployment pipelines, and operating tooling in production


* Strong grounding in observability and production debugging, with hands-on experience using metrics, logs, and traces (e.g. Prometheus, Grafana, OpenTelemetry)


* Experience validating the quality of AI-generated output, and a practical approach to knowing when it can be trusted and when it cannot


* Experience in MLOps or data engineering, ideally including integrating AI systems with data pipelines and infrastructure.






APPLICATION PROCESS
* Talent Partner Screen Call


* Hiring Manager Interview


* Technical Interview

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’

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