The Role
Build and deploy production customer solutions using Telnyx communications APIs, WebRTC, AI voice, LLMs, and wireless technologies. Lead technical discovery, architecture, POCs, launches, observability, model routing, integrations, troubleshooting, and customer handoff. Deploy containerized services on Kubernetes, operate LLM gateways, design high-concurrency event-driven systems, and collaborate with Product and Engineering. The role is customer-facing, based in Hong Kong, and involves travel across Greater China and APAC.
Summary Generated by Built In
About Telnyx
Telnyx is an industry leader that's not just imagining the future of global connectivity—we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network, to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications.
We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team.
Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers.
The Role
We're building a local Enterprise Sales Pod in Hong Kong — one AE and one Forward Deployed Engineer (FDE), working together to build a Telnyx enterprise business in your market. You'll embed directly with enterprise customers to architect and ship production systems on Telnyx's global network — voice, messaging, AI, and wireless.
This isn't about demoing products. It's about building real solutions that work at scale.
You'll work side-by-side with a dedicated Enterprise AE — not a demo resource, but a commercial partner who owns the named-account list, builds executive relationships, and closes the deal. You own the technical side: discovery, architecture, POC, and production go-live. You win together. No throw-over-the-wall.
The Pod Model
Enterprise AE — owns the named-account list, builds executive relationships, gets in the room, owns commercial qualification and close, expands the account.
Forward Deployed Engineer — owns technical discovery, designs the architecture, builds the POC when gated, gets the first workload live, removes blockers and finds the next workload.
We sell the workload, not the SKU. Customers buy a production outcome — an AI contact center, a SOC/NOC agent, global communications, connected mobility, or enterprise inference — that runs on Telnyx primitives (voice, messaging, numbers, wireless, Voice AI, inference, agents, connectivity). You lead with the outcome conversation, not a product menu.
What You'll Do
• Embed with enterprise customers to understand their communications workflows, AI use cases, and integration challenges firsthand
• Build and deploy custom implementations: AI Voice Assistants, Telnyx APIs (Voice, Messaging, Fax, Wireless), WebRTC
• Run open-weight LLMs in customer environments — consume GLM, Kimi, DeepSeek, Qwen, and MiniMax through Telnyx Inference (OpenAI-compatible API; there's no model infrastructure for you to run), or deploy self-hosted stacks (Llama, Mistral, and region-specific models like CKIP-LLO, FlagAlpha, or other Cantonese/Chinese-language sovereign models) behind your own serving engine when air-gapped or sovereign-cloud requirements demand it
• Deploy and operate LiteLLM as the model gateway in customer environments: a unified OpenAI-compatible interface across self-hosted open-weight models and hosted providers, with routing, load balancing, retries and fallbacks, rate limits, and per-team virtual keys
• Instrument and govern LLM usage through the gateway — cost tracking and budgets, caching, logging and observability (OpenTelemetry, Langfuse, or similar), and guardrails — so customers can see and control what their AI workloads are doing
• Wire production observability for everything you ship — metrics, logs, traces, dashboards, and alerting (e.g. Prometheus + Grafana for metrics, OpenTelemetry for traces, Graylog or ELK for logs — or the customer's existing stack) — so you and the customer's ops team both know what "healthy" looks like and what pages whom when it isn't
• Design model routing strategies for real-time voice workloads, balancing latency, cost, and quality, with sane fallback behavior when a provider degrades
• Make the build-vs-buy case between self-hosted open-weight models and hosted frontier APIs, and keep the customer's application code portable across both
• Adapt models to customer domains: prompt and RAG pipelines and evaluation harnesses for English, Cantonese, and Mandarin language use cases and Hong Kong/APAC-specific regulatory environments (PDPO, data localization, Mainland China cross-border data transfer)
• Lead POCs, pilots, and production launches from whiteboard to go-live
• Own customer outcomes — stay engaged until the solution is live and stable
• Collaborate directly with Product and Engineering to shape the roadmap based on field insights from Hong Kong and the broader Greater China/APAC region
We're building a local Enterprise Sales Pod in Hong Kong — one AE and one Forward Deployed Engineer (FDE), working together to build a Telnyx enterprise business in your market. You'll embed directly with enterprise customers to architect and ship production systems on Telnyx's global network — voice, messaging, AI, and wireless.
This isn't about demoing products. It's about building real solutions that work at scale.
You'll work side-by-side with a dedicated Enterprise AE — not a demo resource, but a commercial partner who owns the named-account list, builds executive relationships, and closes the deal. You own the technical side: discovery, architecture, POC, and production go-live. You win together. No throw-over-the-wall.
The Pod Model
Enterprise AE — owns the named-account list, builds executive relationships, gets in the room, owns commercial qualification and close, expands the account.
Forward Deployed Engineer — owns technical discovery, designs the architecture, builds the POC when gated, gets the first workload live, removes blockers and finds the next workload.
We sell the workload, not the SKU. Customers buy a production outcome — an AI contact center, a SOC/NOC agent, global communications, connected mobility, or enterprise inference — that runs on Telnyx primitives (voice, messaging, numbers, wireless, Voice AI, inference, agents, connectivity). You lead with the outcome conversation, not a product menu.
What You'll Do
• Embed with enterprise customers to understand their communications workflows, AI use cases, and integration challenges firsthand
• Build and deploy custom implementations: AI Voice Assistants, Telnyx APIs (Voice, Messaging, Fax, Wireless), WebRTC
• Run open-weight LLMs in customer environments — consume GLM, Kimi, DeepSeek, Qwen, and MiniMax through Telnyx Inference (OpenAI-compatible API; there's no model infrastructure for you to run), or deploy self-hosted stacks (Llama, Mistral, and region-specific models like CKIP-LLO, FlagAlpha, or other Cantonese/Chinese-language sovereign models) behind your own serving engine when air-gapped or sovereign-cloud requirements demand it
• Deploy and operate LiteLLM as the model gateway in customer environments: a unified OpenAI-compatible interface across self-hosted open-weight models and hosted providers, with routing, load balancing, retries and fallbacks, rate limits, and per-team virtual keys
• Instrument and govern LLM usage through the gateway — cost tracking and budgets, caching, logging and observability (OpenTelemetry, Langfuse, or similar), and guardrails — so customers can see and control what their AI workloads are doing
• Wire production observability for everything you ship — metrics, logs, traces, dashboards, and alerting (e.g. Prometheus + Grafana for metrics, OpenTelemetry for traces, Graylog or ELK for logs — or the customer's existing stack) — so you and the customer's ops team both know what "healthy" looks like and what pages whom when it isn't
• Design model routing strategies for real-time voice workloads, balancing latency, cost, and quality, with sane fallback behavior when a provider degrades
• Make the build-vs-buy case between self-hosted open-weight models and hosted frontier APIs, and keep the customer's application code portable across both
• Adapt models to customer domains: prompt and RAG pipelines and evaluation harnesses for English, Cantonese, and Mandarin language use cases and Hong Kong/APAC-specific regulatory environments (PDPO, data localization, Mainland China cross-border data transfer)
• Lead POCs, pilots, and production launches from whiteboard to go-live
• Own customer outcomes — stay engaged until the solution is live and stable
• Collaborate directly with Product and Engineering to shape the roadmap based on field insights from Hong Kong and the broader Greater China/APAC region
• Create clear technical documentation, runbooks, and maintainable solutions for handoff
• Troubleshoot and resolve complex integration issues alongside customer teams
What We're Looking For
• CS degree or equivalent experience
• 3+ years building and shipping production software — you've written code that real users depended on, you've been on-call for it, and you've debugged it when things broke. (A consulting background counts if this is also true of you.)
• Proficiency in multiple languages: Python, Node.js/TypeScript, Go — you're more dangerous in some than others. (Telnyx Edge Compute — functions and stateful actors — is TypeScript, so that one pulls double duty.)
• Practical understanding of what breaks in front of a model in production: provider rate limits and quotas, timeout and retry behavior, streaming, token accounting and cost attribution, and the failure modes that only show up under concurrency
• Comfortable deploying containerized services on Kubernetes, with secrets management, config, and upgrades as part of the deployment story
• You've wired observability and been paged because of it — Prometheus + Grafana, OpenTelemetry, Graylog, ELK, or equivalent. You know what to monitor, what to alert on, and what "healthy" looks like
• High-concurrency experience — Kafka, message queues, or event streams at real scale. When throughput spikes you know what breaks — consumer lag, backpressure, hot partitions, rebalance stalls — and what absorbs it: partitioning, consumer groups, parallelism up to your partition count
• You've built APIs from scratch, not just consumed them — OpenAPI spec, REST/GraphQL design, auth, rate limiting, versioning, idempotency
• Event-driven thinking and cloud-native instincts
• Exposure to SIP, WebRTC, or real-time voice/messaging systems
• Self-sufficient by default — there's no engineering team behind you. You read the code and the docs, ask the customer (not your manager), and make sound engineering judgment calls on your own
• Customer-facing engineering experience — you can run discovery with a customer's engineers and present to their executives in the same week
• Ability to translate "it's not working" into root cause
• Comfortable working on customer sites and in high-stakes technical conversations
• Excellent written and verbal communication in English and Chinese (Cantonese and/or Mandarin). You can run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams.
• Based in Hong Kong, or willing to relocate — this is a hybrid role with travel across Hong Kong and the broader Greater China/APAC region
• Legally authorized to work in Hong Kong, or eligible for sponsorship
Bonus Points For
• Experience with AI voice assistants, STT/TTS, or LLM-based conversational systems
• Building eval sets for a specific domain
• Hands-on production experience with an LLM gateway — LiteLLM, Portkey, Kong AI Gateway, or an in-house OpenAI-compatible proxy — including config-driven model definitions, routing and fallback rules, and virtual key management
• Familiarity with the open-weight model landscape and the trade-offs between regional and multilingual models, including Cantonese/Chinese-language models and Greater China sovereign AI initiatives
• Experience with an inference serving engine behind the gateway — vLLM, SGLang, or TGI for production serving; Ollama for lightweight on-prem — and sizing GPU capacity for self-hosted models (KV-cache footprint, concurrent batch size, and context length against VRAM)
• SQL proficiency (Postgres, MySQL, Oracle)
• ETL and data wrangling experience
• CI/CD pipeline design and automation
• Background in telecom, CPaaS, or high-growth SaaS
• Troubleshoot and resolve complex integration issues alongside customer teams
What We're Looking For
• CS degree or equivalent experience
• 3+ years building and shipping production software — you've written code that real users depended on, you've been on-call for it, and you've debugged it when things broke. (A consulting background counts if this is also true of you.)
• Proficiency in multiple languages: Python, Node.js/TypeScript, Go — you're more dangerous in some than others. (Telnyx Edge Compute — functions and stateful actors — is TypeScript, so that one pulls double duty.)
• Practical understanding of what breaks in front of a model in production: provider rate limits and quotas, timeout and retry behavior, streaming, token accounting and cost attribution, and the failure modes that only show up under concurrency
• Comfortable deploying containerized services on Kubernetes, with secrets management, config, and upgrades as part of the deployment story
• You've wired observability and been paged because of it — Prometheus + Grafana, OpenTelemetry, Graylog, ELK, or equivalent. You know what to monitor, what to alert on, and what "healthy" looks like
• High-concurrency experience — Kafka, message queues, or event streams at real scale. When throughput spikes you know what breaks — consumer lag, backpressure, hot partitions, rebalance stalls — and what absorbs it: partitioning, consumer groups, parallelism up to your partition count
• You've built APIs from scratch, not just consumed them — OpenAPI spec, REST/GraphQL design, auth, rate limiting, versioning, idempotency
• Event-driven thinking and cloud-native instincts
• Exposure to SIP, WebRTC, or real-time voice/messaging systems
• Self-sufficient by default — there's no engineering team behind you. You read the code and the docs, ask the customer (not your manager), and make sound engineering judgment calls on your own
• Customer-facing engineering experience — you can run discovery with a customer's engineers and present to their executives in the same week
• Ability to translate "it's not working" into root cause
• Comfortable working on customer sites and in high-stakes technical conversations
• Excellent written and verbal communication in English and Chinese (Cantonese and/or Mandarin). You can run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams.
• Based in Hong Kong, or willing to relocate — this is a hybrid role with travel across Hong Kong and the broader Greater China/APAC region
• Legally authorized to work in Hong Kong, or eligible for sponsorship
Bonus Points For
• Experience with AI voice assistants, STT/TTS, or LLM-based conversational systems
• Building eval sets for a specific domain
• Hands-on production experience with an LLM gateway — LiteLLM, Portkey, Kong AI Gateway, or an in-house OpenAI-compatible proxy — including config-driven model definitions, routing and fallback rules, and virtual key management
• Familiarity with the open-weight model landscape and the trade-offs between regional and multilingual models, including Cantonese/Chinese-language models and Greater China sovereign AI initiatives
• Experience with an inference serving engine behind the gateway — vLLM, SGLang, or TGI for production serving; Ollama for lightweight on-prem — and sizing GPU capacity for self-hosted models (KV-cache footprint, concurrent batch size, and context length against VRAM)
• SQL proficiency (Postgres, MySQL, Oracle)
• ETL and data wrangling experience
• CI/CD pipeline design and automation
• Background in telecom, CPaaS, or high-growth SaaS
• Experience with sovereign or on-prem cloud deployments and Hong Kong/APAC regulatory frameworks (PDPO, Hong Kong data localization, Mainland China PIPL and CSL cross-border data transfer requirements, Office of the Government Chief Information Officer cloud guidelines, APAC cross-border data transfer frameworks)
• Security mindset (IAM, encryption, audit logging)
#LI-RH1
Skills Required
- Computer science degree or equivalent experience
- At least 3 years building and shipping production software
- Proficiency in Python, Node.js or TypeScript, and Go
- Practical production experience with LLM rate limits, quotas, retries, streaming, token accounting, cost attribution, and concurrency failures
- Experience deploying containerized services on Kubernetes
- Experience with secrets management, configuration, and service upgrades
- Production observability experience with Prometheus, Grafana, OpenTelemetry, Graylog, ELK, or equivalent
- High-concurrency experience with Kafka, message queues, or event streams
- Experience building APIs, including OpenAPI, REST or GraphQL, authentication, rate limiting, versioning, and idempotency
- Event-driven and cloud-native engineering experience
- Exposure to SIP, WebRTC, or real-time voice and messaging systems
- Customer-facing engineering experience, including technical discovery and executive presentations
- Ability to troubleshoot complex integrations and identify root causes
- Excellent written and verbal communication in English and Chinese, Cantonese and/or Mandarin
- Comfort working on customer sites and in high-stakes technical conversations
- Based in Hong Kong or willing to relocate
- Legally authorized to work in Hong Kong or eligible for sponsorship
- Experience with AI voice assistants, speech-to-text, text-to-speech, or conversational LLM systems
- Experience operating an LLM gateway such as LiteLLM, Portkey, Kong AI Gateway, or an in-house proxy
- Experience with vLLM, SGLang, TGI, or Ollama
- SQL proficiency with Postgres, MySQL, or Oracle
- ETL and data wrangling experience
- CI/CD pipeline design and automation experience
- Telecom, CPaaS, or high-growth SaaS experience
- Experience with sovereign or on-premise cloud deployments and Hong Kong/APAC regulatory frameworks
- Security experience with IAM, encryption, and audit logging
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The Company
What We Do
Telnyx delivers voice, messaging and more for applications and next-generation communications companies. Offering a communications platform that provides global carrier-grade services, Telnyx maintains an international, private IP network and grants its customers unprecedented control over their communications through its innovative portal and RESTful API. Telnyx products include voice (elastic SIP trunking, global number search, and telephony data), programmatic messaging, wireless (mobile IoT), embedded communications (WebRTC) and automated networking. Customers provision services a la carte and pay by usage for scalable, on-demand communications.
