Software Engineer, Voice AI / Backend

Clera getclera.com Open

On-site Berlin Full-time Mid-level Backend Engineering

At a glance

Mid-level Backend Engineering role at Clera. Berlin · full-time · €85,000–€160,000 base.

SalaryStated by Clera

€85,000 – €160,000

Base salary for this role, in EUR per year, as published in the posting.

RoleBackend Engineering

SeniorityMid-level

LocationBerlin

WorkplaceOn-site

EmploymentFull-time

Base pay€85,000–€160,000

PostedNov 2, 2026

Role brief

techroles summary, based on the employer's posting.

What you'll do

Build production voice AI with retrieval, model selection, and checks on transcription quality
Design and run call scheduling that handles simultaneous work, time zones, retries, and provider limits
Keep customer context consistent as agents move between calls, messages, and email
Create tools for agent setup, troubleshooting, and links to CRMs, calendars, and email
Make failures easier to trace and help calls, workers, and providers recover cleanly

What you bring

You have shipped and owned distributed systems and taken product projects through delivery
You have production experience with Python, FastAPI, or TypeScript
You have worked with real-time or audio systems and deployed LLM, AI model, or agent software
You can design or troubleshoot concurrency, load balancing, and fault tolerance

Who this fits

This mid-level, end-to-end engineering role suits someone comfortable owning production systems and making reliability tradeoffs. It is based on-site in Berlin; visa sponsorship and relocation support are available.

From the employer

About the Role

Join a small, fast-moving engineering team building voice AI agents for customer-facing workflows. You will own projects end-to-end across applied AI, real-time audio, and distributed systems, helping turn complex customer needs into reliable production software.

What You'll Do

Build reliable voice AI systems, including retrieval-augmented generation, dynamic model routing, and evaluation of transcription systems.
Design and operate a distributed call scheduler that manages concurrency, race conditions, time zones, retries, and provider limits.
Extend agents across voice, messaging, and email, maintaining shared memory and state across real-time and asynchronous conversations.
Develop memory and reasoning systems that preserve context through customer workflows.
Build AI-assisted tools for configuring agents, diagnosing issues, and connecting to business systems such as CRMs, calendars, and email.
Improve observability and resilience by making failures traceable and ensuring graceful recovery when calls, workers, or providers fail.

What We're Looking For

Production experience building and owning distributed systems, with a track record of shipping product software and delivering projects end-to-end.
Strong software fundamentals and experience with Python, FastAPI, or TypeScript in production systems.
Experience with real-time systems, audio processing, or voice infrastructure, and with production LLM, AI model, or agentic systems.
Experience with PostgreSQL, Redis, or similar data stores, plus cloud infrastructure on AWS, GCP, or Azure.
Ability to design or debug systems involving concurrency, load balancing, and fault tolerance.
Familiarity with tools such as LiveKit, Temporal, message queues, workflow orchestration, React, and observability platforms is valuable.
Independent, action-oriented approach, sound judgment about code quality and reliability, and a focus on team and customer outcomes.