Member of Technical Staff — AI / Software Engineering (US)

About Cekura

Cekura is building the infrastructure for self-improving conversational agents.

Teams use Cekura to test, monitor, debug, and improve AI agents across voice, chat, SMS, phone, and web. We help them catch failures in latency, barge-in, tool calls, hallucinations, instruction-following, regressions, and production workflows.

We're YC F24, growing fast, backed by top investors, and working with teams deploying AI agents in the real world.

About the Role

We're hiring a Member of Technical Staff to build the core of Cekura — the simulation engines, evaluation systems, and observability pipelines that our customers rely on to ship agents with confidence.

We deliberately don't split this role into "software engineer" vs. "AI engineer." At Cekura, the interesting problems live at the boundary: real-time voice infrastructure meets LLM-as-judge evaluation, distributed systems meet RL-style self-improvement loops for agents, telephony meets audio and speech analysis — ASR quality, barge-in, latency, prosody — and classic NLP meets frontier agentic behavior. You'll work across that whole surface.

What You'll Do

Build the testing and simulation engine

Design and ship systems that simulate thousands of realistic conversations against customer agents — across voice, chat, and phone — with control over personas, interruptions, background noise, and edge cases.

Push the frontier of agent evaluation

Build LLM-powered evaluators, metrics, and self-improvement loops that catch failures humans miss — and make them accurate, fast, and trustworthy at scale.

Do applied audio and speech research

Go beyond the transcript. Separate background noise from actual speech, and map the paralinguistic layer of conversation into structured signals — emotion and tone, silences and hesitations between words, speaking rate, overlaps and interruptions — so agents can be evaluated on how something was said, not just what was said.

Own real-time voice infrastructure

Work with SIP, WebRTC, WebSockets, STT/TTS pipelines, and providers like Twilio, Vapi, Retell, LiveKit, and Pipecat. Latency, barge-in, and audio quality are first-class problems here.

Ship end-to-end

Take features from design to production. You'll own the full stack of what you build — backend, infra, evals, and the product surface customers touch.

Shape how we build

We're a small, senior team. Your architectural decisions, code standards, and technical taste will compound as the team grows.

About You

- You're a strong generalist engineer who's excited to work across systems and AI, not someone looking to stay in one lane.

- You've built and operated production systems and care about reliability, latency, and correctness.

- You're fluent in Python and comfortable picking up whatever the problem needs.

- You have strong instincts about LLMs, where they fail, how to evaluate them, how to build reliable systems on top of unreliable models.

- You like ambiguity, move fast, and raise the bar for the people around you.

- Bonus points- if you are an ex-founder or aspire to be a founder in the future.

Minimum Qualifications

- Strong coding ability in Python, TypeScript, or Go.

- Experience with at least one of: distributed systems, real-time infrastructure, or LLM-based products.

- Strong written and verbal communication.

Nice to Have

- Hands-on experience with LLM evals, agent frameworks, or AI observability.

- Experience with voice AI: Twilio, SIP, WebRTC, Vapi, Retell, LiveKit, Pipecat, or STT/TTS pipelines.

- Experience at an early-stage startup or as an early engineer at a dev-tool, infra, or AI company.

- Open-source contributions or public technical work.

This Might Not Be for You If

- You want a narrowly scoped role with a fixed tech stack.

- You prefer working only on models, or only on infrastructure, never both.

- You need rigid processes or heavy structure.

- You don't want to work in-person in SF.

- You're looking for a 9-to-5. We're in-person in SF, we work long hours including most weekends, and the pace is intense. We're building fast and we're honest about what that takes.

Why Cekura

- Work on the hardest problems in AI agent reliability, simulation, voice evals, and real-time voice at scale.

- Join a 12-person engineering team post-seed, early enough to matter, funded enough to move fast.

- Work directly with founders and a highly technical team.

- Meaningful equity, competitive compensation, and fast growth.

- Medical, dental, vision, team lunches, and dinners.