Artificial Intelligence

• Help define Talent Engineering in Ukraine: build AI agents, workflows, and analytics that transform how high-bar recruiting gets done
• Build the AI systems that make our Talent Partners unstoppable
• You'll know this role is working when: Time-to-first-candidate drops from ~2 weeks to 2-3 days
• When a search opens, the first qualified candidate hits the client within days, not weeks
• Talent Partners run ~10 high-signal interviews per role, up from ~5, because you've taken manual sourcing off their plate
• 3-4 sourcing hypotheses run in parallel from week one - no more sequential testing
• Team Tailor becomes the single source of truth
• You'll prototype, benchmark, and ship weekly, and document what works and what doesn't
• Expect to shadow live searches for the first 2-3 weeks before making any changes

Talent Engineer – AI Automation

• Learn and be supervised/mentored by Senior and Principal team members on multiple team efforts.
• Build a natural-language interface for cluster operations.
• Generate an MCP server from OpenAPI specs and connect it to an LLM reasoning agent that can understand operator requests, validate API calls, and execute them safely.

AI Intern

• Launch and iterate on product experiments daily and weekly across the funnel.
• Own and manage the experimentation backlog (prioritization, planning, execution).
• Write clear PRDs and experiment briefs for fast developer execution.
• Generate experiment ideas using UX research, funnel analysis, and data insights (via Mixpanel and Claude).
• Own the full experiment lifecycle (idea → build → release → measure → decision).
• Work directly with developers, providing continuous feedback to ensure fast delivery and accuracy.
• Manage release flow across dev, staging, and production environments.
• Ensure accurate tracking, analytics, and A/B test setup (via GrowthBook and Mixpanel).
• Monitor performance and deliver daily/weekly insights and iteration decisions.
• Control the end-to-end experimentation pipeline, ensuring speed, quality, and KPI alignment.

Growth Manager

• Make performance a core company competency across our database and AI workloads.
• Set the performance engineering strategy—defining benchmarks, realistic workloads, regression detection and gating, and clear executive-ready reporting.
• Partner with Engineering, Solutions Verification, and Product to ensure we deliver predictable performance at scale.
• Influence product direction by identifying systemic bottlenecks, shaping architectural and roadmap decisions, and leading cross-team initiatives.
• Build and maintain repeatable end-to-end benchmarks for database and AI workloads.
• Evaluate throughput, latency, concurrency, scalability, and stability across OLTP/OLAP and mixed workloads.
• Measure and optimize performance for GPU/CPU inference pipelines, model serving, and data/feature pipelines; assess cost/performance tradeoffs.
• Develop harnesses, scripts, dashboards, and reproducible environments to run benchmarks consistently.
• Produce clear reports, identify bottlenecks, and recommend fixes.
• Partner with database engineers, AI engineers, the field teams and product management to define performance goals and acceptance criteria.
• Establish standards for test hygiene, statistical rigor, hardware normalization, and benchmark governance.

Principal Performance Engineer, Database & AI Benchmarking

• Lead both the technical and human sides of AI transformation — building solutions, running enablement programmes, and keeping our AI Champions network thriving across Europe.
• Design, build, and iterate on internal AI tools and automation solutions that solve real operational problems across the organisation.
• Plan and deliver engaging AI workshops and training programmes tailored to varying levels of technical fluency across six European markets.
• Manage and grow the AI Champions network, acting as the connective tissue between local market advocates and the central AI Transformation Team.
• Partner with the engineering team to translate complex AI capabilities into accessible, practical use cases for non-technical stakeholders.
• Track and report on AI adoption metrics across markets, identifying gaps and opportunities to accelerate enablement.
• Stay close to the fast-moving AI landscape, surfacing relevant tools, models, and approaches that could benefit Aceve’s teams and products.

See all jobs on JobTailor

Talent Engineer – AI Automation

AI Intern

Growth Manager

Principal Performance Engineer, Database & AI Benchmarking

AI Transformation Engineer