This isn't about demoing products; it's about building real solutions that work at scale.
You'll sit at the intersection of software engineering, AI infrastructure, telecommunications, and customer success — working directly with customer engineering and technical leadership teams to understand requirements, architect solutions, build integrations, and take them from POC through production.
A major focus will be helping customers deploy real-time AI and communications workloads, including AI Voice Assistants, LLM inference, open-weight models, and applications requiring low latency, reliability, and regional data processing.
Responsibilities
Embed with customers to understand their technical requirements, AI use cases, and integration challenges
Architect and build custom production solutions using Telnyx's Voice, Messaging, Wireless, WebRTC, AI, and Edge Compute platforms
Build and deploy AI Voice Assistants, conversational AI, and LLM-powered applications
Deploy and operate LLM infrastructure, including open-weight models and LiteLLM or comparable gateways
Design model routing, fallback, observability, and cost strategies for production AI workloads
Build RAG pipelines, prompt architectures, evaluations, and model integrations
Deploy containerized services on Kubernetes and work with customer infrastructure teams on production environments
Troubleshoot complex issues across APIs, networking, SIP, WebRTC, AI inference, and customer infrastructure
Lead technical discovery, architecture sessions, POCs, pilots, and production launches from whiteboard to go-live
Own customer outcomes through deployment, stabilization, and handoff
Partner with Product and Engineering to turn customer feedback into product improvements
Create technical documentation, runbooks, and reference architectures
Help customers navigate data residency, security, privacy, and compliance requirements across APAC
What We're Looking For
CS degree or equivalent practical experience
3+ years building software, infrastructure, or working in technical consulting
Strong proficiency in one or more of Python, Node.js, or Go
Hands-on experience deploying LLM applications or AI infrastructure in production
Experience with LiteLLM or a comparable LLM gateway, including routing, fallbacks, rate limits, and observability
Comfortable with Kubernetes, Docker, APIs, cloud infrastructure, and production operations
Exposure to SIP, WebRTC, VoIP, real-time communications, or messaging
Strong understanding of production AI challenges including latency, concurrency, provider limits, retries, streaming, and cost
Ability to diagnose complex technical problems and translate customer requirements into practical solutions
Comfortable working directly with customers and leading technical architecture discussions
Strong communication skills with the ability to explain complex technology to both technical and non-technical audiences
Based in Sydney or willing to relocate
Legally authorized to work in Australia, or eligible for sponsorship
Bonus Points
AI Voice Assistants, conversational AI, STT/TTS, or real-time AI experience
Experience with open-weight models, vLLM, SGLang, TGI, or Ollama
LLM fine-tuning, RAG, evaluation, or inference optimization
Experience sizing and optimizing GPU infrastructure
Background in telecom, CPaaS, cloud/AI infrastructure, or high-growth SaaS
Enterprise, on-prem, or customer-controlled infrastructure experience
Experience with regulated industries or APAC data residency requirements
Strong DevOps/security fundamentals
Experience working across multiple APAC markets
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