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3 дня назад

Staff AI Engineer (AI Labs)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior/lead
Английский
b2
Страна
UK/Spain/Romania
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Staff AI Engineer (AI Labs) (LLM/Agentic AI): Building evaluation harnesses, sandboxes, and focused prototypes to assess emerging AI technologies for a global fintech company with an accent on benchmarking, experimental design, security, and production readiness. Focus on comparing models and tools under realistic constraints, documenting trade-offs, and coordinating validated technologies into engineering hand-offs.

Location: Hybrid in Madrid, Barcelona, London, or Bucharest

Company

Financial infrastructure company powering global commerce and payment ecosystems across more than 60 countries.

What you will do

  • Scout, prototype, and evaluate emerging AI models, tools, frameworks, agentic systems, vector databases, and orchestration technologies.
  • Design evaluation environments with datasets, prompts, scenarios, telemetry, regression tracking, and benchmark coverage.
  • Build focused prototypes to assess architecture, integration patterns, security boundaries, operational constraints, and failure modes.
  • Compare vendor and open-source solutions across quality, cost, latency, security, and integration complexity.
  • Write decision memos and readiness guidance, then coordinate validated technologies with engineering teams for productionization.
  • Work with Security, Legal, Compliance, and AI teams on risk assessments, governance, guardrails, and reusable standards.

Requirements

  • 8+ years of software engineering experience, including significant senior or Staff-level scope.
  • Deep hands-on experience building and evaluating LLM-based systems and modern AI tooling.
  • Experience with agentic or multi-step AI systems involving tool use, orchestration, state, retrieval, or external integrations.
  • Strong software engineering, cloud infrastructure, observability, telemetry, testing, benchmarking, reliability, and distributed-systems skills.
  • Experience designing evaluation datasets and benchmarks, including labelling, holdout discipline, LLM-as-judge methods, human evaluation, and statistical reasoning.
  • Ability to communicate technical results clearly, influence without authority, and make trade-off decisions across quality, latency, cost, and vendor lock-in.

Nice to have

  • Experience with AWS AI tooling and external copilots.
  • Experience mentoring engineers, participating in technical hiring, and sharing knowledge through talks or meetups.

Culture & Benefits

  • Flexible schedules focused on impact and productivity rather than fixed hours.
  • Hybrid collaboration combining self-managed focus time with in-person connection.
  • Opportunity to work on applied AI challenges in the fintech industry.
  • Work from anywhere while traveling for up to three months per year.
  • Referral bonus program and country-specific benefits.

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