13 дней назад
Senior AI Engineer — Exploration & Prototyping
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior AI Engineer — Exploration & Prototyping (AI/LLM systems): Exploring agent orchestration, real-time transport, memory protocols, interoperability standards, and LLM infrastructure through focused technical spikes and prototypes with an accent on evidence-based evaluation, latency, cost, and failure measurement. Focus on reading unfamiliar codebases, designing benchmarks, making build-versus-adopt recommendations, and handing defensible conclusions to production teams.
Company
develops cloud-based video products for live, on-demand, and real-time experiences used by more than 1,000 organizations.
What you will do
- Run technical spikes evaluating agent orchestration frameworks, real-time transport, memory protocols, interoperability standards, LLM selection and routing, evaluation harnesses, and production libraries.
- Build focused prototypes to prove or disprove technical approaches and de-risk platform decisions.
- Read unfamiliar framework codebases and assess their practical suitability beyond documented capabilities.
- Design benchmarks and measurement harnesses covering latency, cost, and failure behavior.
- Own build-versus-adopt recommendations and document evidence, rejected options, trade-offs, and the cost of being wrong.
- Hand findings to platform, research, and forward-deployed teams while tracking relevant developments in agentic infrastructure and AI tooling.
Requirements
- B.Sc. in Computer Science or an equivalent technical field.
- 7+ years of industry experience in software, ML, or research engineering, including ownership of production systems.
- Strong Python skills and breadth across backend services, runtime, infrastructure, and ML-adjacent systems.
- Experience designing benchmarks or measurement harnesses and making technical evaluations that led to decisions.
- Experience with real-time, streaming, or latency-sensitive systems, plus hands-on experience with LLMs and agentic systems.
- Experience in a fast-moving SaaS company and cloud environments such as AWS, GCP, or Azure; ability to work independently as an individual contributor.
Nice to have
- Experience with Pipecat, LiveKit Agents, WebRTC, media transport, or streaming infrastructure.
- Experience with agent memory systems, MCP, or agent interoperability standards.
- Ability to evaluate research literature and translate it into practical recommendations.
- Open-source contributions, public technical writing, published evaluations, or early-stage and founding-engineer experience.
- M.Sc. in Computer Science, Machine Learning, or a related field.
Culture & Benefits
- Hybrid and flexible work environment.
- Extended private health insurance, including mental health coverage.
- Personal and professional development programs.
- Occasional cross-company long weekends.
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