SeniorStaff Backend Engineer

Location: Remote USA Canada or London UK
Engagement: Full-time / Long-term project
Compensation: $160K$240K annually meaningful equity
Seniority: Senior / Staff

We are looking for a Senior/Staff Software Engineer to join a rapidly growing technology company building infrastructure for AI-powered voice agents.

The product helps companies test and improve their AI voice agents at scale. The platform can automatically run thousands of simulated calls using different accents tones speaking styles personalities and scenarios then analyze the conversations and identify bugs failures and unexpected behavior.

The company is experiencing rapid growth and is now scaling its infrastructure from approximately 30K concurrent voice calls toward 100K200K concurrent calls.

A major upcoming initiative is the development of a purpose-built database for conversational AI designed to efficiently store process query and retrieve massive volumes of voice-agent interaction data.

Were looking for someone who has genuinely built data infrastructure at scale ideally as a primary author architect or technical owner of a database queue storage system streaming platform or other large-scale data system.

• Design and build a purpose-built database for conversational AI data including storage architecture indexing ingestion query paths and retrieval at scale.
• Scale simulation infrastructure from approximately 30K toward 200K concurrent voice calls.
• Architect systems for high availability graceful degradation and 99.99% uptime.
• Own critical backend services built primarily with TypeScript/ and Python.
• Work with technologies across real-time voice and AI infrastructure including LiveKit Temporal STT/TTS systems and LLM tooling.
• Build reliable pipelines for telephony events recordings transcripts evaluations and call outcomes.
• Improve distributed tracing and production observability using technologies such as OpenTelemetry and SigNoz.
• Diagnose and eliminate performance bottlenecks across high-throughput distributed systems.
• Make architectural decisions around scalability reliability latency storage and infrastructure costs.
• Ship quickly measure production behavior and continuously iterate. The engineering team currently deploys to production multiple times per day.

• 5 years of software engineering experience with strong backend or infrastructure expertise.
• Proven experience building a database queue storage engine streaming system distributed data platform or comparable large-scale infrastructure.
• Ideally you were a primary author architect or technical owner rather than simply a user or contributor.
• Strong knowledge of distributed systems including partitioning replication concurrency consistency failure recovery backpressure and graceful degradation.
• Experience scaling infrastructure under significant real-world production load.
• Ability to discuss previous systems quantitatively for example requests/events per second concurrency p95/p99 latency data volumes availability cluster size or cost improvements.
• Strong backend development experience. TypeScript/ and Python are used on the project but engineers from other strong infrastructure backgrounds are welcome.
• Strong understanding of production monitoring observability and distributed tracing.
• High level of ownership and ability to operate effectively in a fast-moving environment.
• AI-native mindset: actively using modern AI tools to accelerate engineering debugging research and development.
• Strong bias to action comfortable building the smallest working solution shipping it learning from production and iterating.

• Database internals / storage engine development
• Distributed databases
• Kafka Pulsar Redpanda or similar messaging infrastructure
• Streaming or high-throughput ingestion systems
• Query engines and indexing
• Observability infrastructure
• OpenTelemetry / SigNoz
• WebRTC / LiveKit
• Telephony SIP or RTP
• Voice or audio processing
• STT/TTS infrastructure
• LLM infrastructure
• Experience at a database data infrastructure observability or developer infrastructure company

1. Short Screening Interview
A brief AI interview (recommended for faster candidate submission)or conversation with a recruitment agency representative to discuss the candidates background relevant experience and fit for the role.

2. Candidate Submission
The candidates profile is submitted to the client. Well notify the candidate once the hiring team confirms whether they would like to proceed.

3. Intro Call 15 minutes
A brief conversation with a team member to assess culture fit interest in systems/infrastructure work ownership mindset and alignment with a fast-paced engineering environment.

4. Coding Interview 30 minutes
An open-book live coding session. Candidates are encouraged to use their preferred AI tools while building something in real time. The focus is on coding fluency speed of prototyping problem-solving and an AI-native engineering workflow.

5. Systems Design Interview #1 60 minutes
Focused on distributed systems database architecture and scalability. The discussion may cover technologies and concepts related to PostgreSQL Redis Kafka and high-scale real-time infrastructure.

6. Systems Design Interview #2 60 minutes
A second technical design interview with another engineer covering a different problem area such as observability voice simulation infrastructure data pipelines or large-scale distributed systems.

7. Paid Work Trial 23 days
A paid trial based on a real engineering problem. This gives both sides an opportunity to evaluate delivery speed technical decision-making communication collaboration and overall fit.

8. Offer & Hiring
Successful candidates receive an offer following the work trial.