Senior Software Engineer (Platform — Backend / AI/ML / Integrations)

Combined role — replaces the former Senior Backend Engineer (Go), Senior AI/ML Engineer, and Integration Engineer listings.

The role. One senior developer role, three specialization tracks. We build voice, desktop, intelligence, and AI combined into a single real-time platform — event-driven, high-throughput, low-latency. You'll build Go services on the event bus, AI/ML services and pipelines, or connector frameworks to CCaaS/CRM/telephony — most engineers here end up touching more than one. This is a startup environment on a fast train: 1-week sprints, Friday demos, fail fast and move forward.

What you'll own. Services on the event bus (NATS-class) · high-throughput transactional data models and WebSocket backends · your track's slice — AI/ML pipelines (RAG, streaming inference, eval) or connectors (CCaaS/CTI, CRM, SIP/RTP) or core platform services · your latency budget · your committed timelines.

Who you are. You consider yourself exceptional — and can show it. Self-starter, hacker, grit, loves to learn, loves winning. You demonstrate ideas easily: a working prototype beats a slide deck every time. You understand requirements and stay locked on them — we work with all-new technology constantly, and you don't get wrapped around shiny objects; you evaluate fast, adopt what earns it, and keep shipping. Fail fast, move forward. A team player who makes and hits committed timelines.

Requirements

• 7+ years backend; 3+ languages across your career. HIGH++ proficiency in GoLang — mandatory and tested; production Go at scale, not dabbled. Medium-strength Python or another scriptable language.

• Event-driven systems in production (NATS / Kafka / Redpanda-class) — you think in pub/sub. Heavy WebSocket, real-time, low-latency.

• Mid-tier or better hands-on AI experience in the code and product — you've built with LLM APIs, embeddings, RAG, or model serving, not just chatted with a bot. And you use AI-assisted development daily to multiply your velocity.

• Strong ++ for data graph / knowledge graph background, or hands-on AI/ML model experience (training, serving, eval).

• Efficiency in development — we deal in speed. You ship clean code fast, unblock yourself, and your estimates hold.

• A master debugger — you read unfamiliar code, a stack trace, or a flaky partner API and see it; you know where the breakpoint goes.

• GCP preferred. Voice (SIP/RTP/SIPREC), CCaaS/CTI, or desktop-adjacent experience a strong plus depending on track.

Track emphases. Backend/Platform: data models, event bus, plugin runtime. AI/ML: deeper Python, production GenAI/NLU, streaming inference, eval frameworks, RAG. Integrations: CCaaS/CTI platforms (Genesys, Amazon Connect, NICE, Five9), CRM connectors, SIP/RTP, fault-tolerant connector design.