# Forward Deployed Engineer, Singapore **Company**: Telnyx **Location**: Singapore **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/telnyx54/jobs/7992741003?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_cbaa8da3-251 ## Description ## The Role We're building a local Enterprise Sales Pod in Singapore , 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. ## Responsibilities - 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 SEA-LION, Merlion, or other Southeast Asian multilingual 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, Mandarin, Malay, and Tamil language use cases and Singapore/APAC-specific regulatory environments (PDPA, data localization, MAS cloud regulations) - 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 Singapore and the broader Southeast Asia region - Create clear technical documentation, runbooks, and maintainable solutions for handoff - Troubleshoot and resolve complex integration issues alongside customer teams ## Requirements - 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. You can run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams. ## Nice to Have - 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 Southeast Asian multilingual models (SEA-LION, Merlion) and APAC 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 Singapore/APAC regulatory frameworks (PDPA, MAS TRM Guidelines for financial services, IMDA cloud regulations, Singapore data localization, ASEAN cross-border data transfer frameworks) - Security mindset (IAM, encryption, audit logging) ## Skills ### Required - Python - Node.js/TypeScript - Go - Kubernetes - Prometheus - Grafana - OpenTelemetry - Graylog - ELK - Kafka - message queues - event streams - OpenAPI spec - REST/GraphQL design - auth - rate limiting - versioning - idempotency - SIP - WebRTC ### Nice to have - AI voice assistants - STT/TTS - LLM-based conversational systems - LiteLLM - Portkey - Kong AI Gateway - vLLM - SGLang - TGI - Ollama - SQL - ETL and data wrangling - CI/CD pipeline design and automation - telecom - CPaaS - high-growth SaaS - sovereign or on-prem cloud deployments --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/telnyx54/jobs/7992741003?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)