About this role
Developers who thrive in client-facing environments and enjoy solving complex architectural challenges independently will find a strong fit in this Forward Deployed Engineer position at Telnyx. Operating out of Stockholm within a local Enterprise Sales Pod alongside an Account Executive, this practitioner takes full ownership of the technical journey from discovery to production go-live for enterprise clients across the Nordics. The team focuses on building scalable voice, messaging, AI, and wireless systems using Telnyx primitives and open-weight models.
Day-to-day responsibilities involve embedding directly with enterprise customers to design custom implementations, deploy AI voice assistants, configure model gateways like LiteLLM, and wire production observability stacks. The role exists to bridge the gap between technical capabilities and enterprise business outcomes, ensuring smooth integrations tailored to regional requirements such as GDPR and EU AI Act compliance. Success in this position requires a self-sufficient engineer who can handle high-concurrency architectures, navigate customer sites, and translate ambiguous technical issues into stable, running systems.
What you will do
- Embed directly with enterprise customers across the Nordics to understand their communications workflows, AI use cases, and integration challenges firsthand.
- Build and deploy custom implementations including AI Voice Assistants, WebRTC solutions, and Telnyx APIs.
- Run open-weight LLMs in customer environments through Telnyx Inference or deploy self-hosted stacks when sovereign-cloud requirements demand it.
- Deploy and operate LiteLLM as a model gateway to handle routing, load balancing, rate limits, and per-team virtual keys.
- Wire production observability for everything shipped using tools like Prometheus, Grafana, OpenTelemetry, and Graylog or ELK.
- Adapt models to customer domains by building prompt and RAG pipelines for Swedish, Danish, Norwegian, and Finnish language use cases.
- Lead technical discovery, architecture design, proofs of concept, and production launches while owning customer outcomes until go-live.
What you need
- Hold a Computer Science degree or possess equivalent professional experience.
- Demonstrate at least three years of experience building and shipping production software that real users depend on.
- Show proficiency in multiple programming languages such as Python, Node.js or TypeScript, and Go.
- Possess a practical understanding of production model constraints including rate limits, streaming, token accounting, and concurrency failure modes.
- Feel comfortable deploying containerized services on Kubernetes with proper secrets management and configuration.
- Bring high-concurrency experience handling Kafka, message queues, or event streams at real scale.
- Demonstrate customer-facing engineering experience running technical discovery with customer engineers and presenting to executives.
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 such as LiteLLM, Portkey, Kong AI Gateway, or an in-house OpenAI-compatible proxy
Skills and tech stack
Questions candidates ask
What is the work location and remote policy for this role?
The role is based in Stockholm, Sweden, or requires a willingness to relocate. It is a hybrid role with travel across the Nordics including Sweden, Denmark, Norway, and Finland.
What does the team structure look like for this position?
You will work in a local Enterprise Sales Pod consisting of one Account Executive and one Forward Deployed Engineer. The Account Executive owns the commercial relationship while you own the technical side from discovery to production go-live.
What tools and models will I be working with?
You will work with Telnyx APIs, open-weight LLMs like GLM, Kimi, DeepSeek, Qwen, and MiniMax through Telnyx Inference, as well as self-hosted stacks like Llama and Mistral. You will also deploy LiteLLM as a model gateway and use observability tools like Prometheus, Grafana, and OpenTelemetry.
What kind of support will I have from engineering?
You will be self-sufficient by default as there is no engineering team behind you. You read the code and docs, ask the customer, and make sound engineering judgment calls on your own, while collaborating directly with Product and Engineering to shape the roadmap.