Senior Software Engineer

We're hiring a Senior Backend Engineer to own high-throughput, real-time systems behind Convin's AI products: voicebots, AI agents, Auto QA and agent assist.

Convin builds AI for contact centers. Our platform serves 100+ enterprise clients across BFSI, edtech and other sectors, handles 50M+ API requests a month, runs 500K+ voicebot calls a day and analyzes 500M+ conversations a year.

You'll design systems end to end, ship them to production, and be on the hook for how they behave at scale. This is a role for an engineer who wants ownership, not tickets.

What you'll work on:

• Real-time voice AI. Build and scale our Go voicebot across WebSocket and SIP, orchestrating STT -> LLM -> TTS with sub-second end-to-end latency at hundreds of thousands of calls a day.
• LLM systems in production. Design RAG pipelines, function calling (CRM updates, calendar booking, payment links) and multi-provider LLM orchestration with fallbacks, caching and guardrails against hallucination.
• Core platform services. Own high-volume services such as our rule engine, job scheduler and notification system, each running millions of operations a day.
• Scale and cost. Profile, tune and right-size services on Kubernetes; cut latency and cloud, LLM and TTS spend without hurting quality.
• Data layer. Model data and optimize queries across PostgreSQL, Redis, ClickHouse and Qdrant.
• Observability and reliability. Instrument services with Prometheus, Grafana and Jaeger; define SLOs, run on-call for what you own, and write blameless postmortems.
• Engineering leadership. Write design docs, review code, mentor SDE1/SDE2 engineers and interns, and raise the bar on code quality.
• Customers. Join technical discussions with enterprise clients when a design needs to fit their telephony, data or compliance constraints.

What we're looking for:

• 4+ years of experience years building backend systems, with at least 1 year owning services in production at meaningful scale.
• Strong in Go (preferred) or Python, with solid grasp of concurrency, networking and memory behavior.
• Hands-on distributed systems experience: queues (Kafka, RabbitMQ or Celery), caching, idempotency, retries, backpressure and graceful degradation.
• Production experience with Kubernetes and Docker on AWS or GCP, including autoscaling and resource tuning.
• Strong PostgreSQL skills: schema design, indexing, query plans; working knowledge of Redis.
• Has shipped at least one LLM-powered feature to real users and can talk about its latency, cost and failure modes.
• Uses metrics, logs and traces to debug, not guesswork.
• Writes clear design docs and can defend trade-offs with numbers.
• Ownership mindset: you've seen a system through launch, incidents and the rewrite after.

Nice to have:

• Real-time audio or voice: WebRTC, SIP, telephony, or STT/TTS providers.
• RAG and vector databases (Qdrant or similar), embeddings, prompt engineering and LLM evaluation.
• ClickHouse, ScyllaDB or Elasticsearch for analytics or high-write workloads.
• Service mesh and infra tooling: Envoy, Istio, Terraform, Helm.
• gRPC and WebSocket services at high connection counts.
• Multi-tenant SaaS architecture, or single-to-multi-tenant migrations.
• Fluency with AI coding tools (Claude Code, Cursor, Copilot) in daily work.
• Startup experience, or having built something from zero to production.

Why Convin:

• Real scale, early. Your code handles millions of conversations from day one, not a demo.
• Frontier problems. Sub-second voice AI, LLM cost and latency, and agentic systems that act on customers' behalf.
• Ownership. Small team, large surface area; you own systems, not tickets.
• Growth. Our backend leads grew from within, from intern to lead.

Hiring process:

• Introductory call
• LLD / machine coding round
• HLD round
• Final interview with the hiring manager

Skills

AWS, Docker, GCP, Go, Kubernetes, PostgreSQL, Python, Redis