Forward Deployed AI Engineer
First seen by Alion on Oct 28, 2026.
About us
Next Dialog automates business communication with AI. Our omnichannel platform handles customer conversations across phone, SMS and messaging: answering questions, booking appointments, qualifying leads and syncing everything to the CRM, 24/7. Our clients range from HVAC installers and real estate brokerages to dental clinics, logistics and energy companies across Poland, Germany, the rest of Europe and the US. We're a small, product-focused team working at the intersection of AI and communication automation, and we're hiring a Forward Deployed AI Engineer to own our AI systems from architecture to live production.
The role
You own AI systems end to end, from architecture to live production. You will:
Build harnesses: test and eval harnesses for LLM and voice pipelines, simulated conversations, and regression suites that catch quality drops before clients see them
Instrument what ships: tracing of LLM and agent calls (prompts, tool calls, tokens, cost, latency), quality monitoring and regression alerts in production
Design and build microservices: new services and integrations that fit into a platform running in production, including MCP servers and tools for our agents and internal tooling
Optimize AI pipelines: latency, cost, accuracy, and reliability, measured with real metrics
Automate everything repetitive: checks, deployments, agent setup, and routine ops, using scripts, agents, and MCP tooling
Design for safety and privacy: prompt injection, PII handling, call-recording consent, human approval for irreversible actions
Own live production: monitor, debug, and fix real campaigns running real calls
What the role is not
Not a research role. No model training from scratch, no TensorFlow/PyTorch.
Not a prompt-only role. Prompts are one tool among evals, tracing, integrations and ops.
Not a frontend role. React/Next.js is in the stack, but it is not where you will spend your days.
Our stack
TypeScript, NestJS, PostgreSQL, React, Next.js · Retell AI, LiveKit, Deepgram, ElevenLabs, Twilio · Gemini/Vertex AI, OpenAI, Anthropic · Langfuse / OpenTelemetry-style tracing · GCP, Terraform, Docker · Cursor, Claude Code, MCP
Must have
4+ years of engineering experience in any server-side language, with a strong track record of designing, running and supporting microservice architectures in live production
Production experience with LLMs: prompting, structured output, tool calling, RAG, evals
Experience building test or eval harnesses and automating pipelines
Experience with LLM observability: tracing prompts, tool calls, tokens, cost and latency, and using traces to find and fix regressions
AI-native workflow: you do most of your tasks through AI agents and know how to build context for them
Hands-on experience with MCP: you have built or wired MCP servers and tools, not only used them
Strong SQL: comfortable analysing call and campaign data in PostgreSQL
Experience with real-time or webhook-driven systems
You design for safety and privacy: prompt injection, PII, consent, guardrails
English B2+
Nice to have
Voice AI experience (Retell, Vapi, LiveKit, Pipecat, telephony, SIP/WebRTC, streaming audio, STT/TTS, turn-taking and interruptions, latency tuning)
Past experience as a team or tech lead
Forward deployed or solutions engineering experience at a startup
GCP, Terraform, on-prem deployments
Hiring process
Online prescreen
Interview
Decision