Forward Deployment Engineer
- Experience
- Senior
- Employment
- Full-time
- Company size
- Startup
Open to DE only. Set where you work from to check your eligibility.
No BS summary
Deployment engineer with 3+ years of experience in production AI integrations and automation workflows. Must have deep LLM experience (prompting, RAG, evaluation, failure modes) and ability to translate business needs into AI workflows. Requires API/webhook integration skills, cloud fundamentals, and strong coding for features/glue code. Must be pragmatic and ownership-driven. Fully remote within Germany.
Core skills
Required skills
Optional skills
ABOUT THE ROLE
This is a hands-on technical role at the intersection of product and customer deployments. You'll sit at the core of a fast-moving AI communication platform — owning end-to-end production rollouts, building integrations, and ensuring customers get reliable, real-world results from day one. Your work will directly shape how the product evolves by feeding field learnings back into engineering and product teams.
The company is a well-funded, seed-stage European startup building AI phone assistants for small and medium-sized businesses. The team is lean (~50 people) and growing rapidly, with a strong engineering culture and a proprietary orchestration layer built in-house with a focus on European data privacy standards.
WHAT YOU'LL DO
- Act as the technical bridge between product and customer setups — translating business requirements into robust, production-ready implementations.
- Lead end-to-end rollouts of AI assistant configurations in production, including workflows, logic, data flows, prompts, and guardrails.
- Implement integrations with third-party systems via APIs and webhooks, covering CRMs, calendars, ticketing, payments, and common auth patterns (OAuth, API keys).
- Develop glue code and small-to-medium features with tests, monitoring, and logging to map customer use cases to production systems.
- Debug live issues across calls, flows, and data pipelines — and ship rapid fixes under production conditions.
- Build reusable templates, deployment playbooks, and best practices to make setups scalable and repeatable across customers.
- Maintain a tight feedback loop with product and engineering by surfacing pain points, feature gaps, and recurring patterns with concrete recommendations.
- Own deployment success and ensure customer setups function reliably in live production call environments.
WHAT WE'RE LOOKING FOR
Must-haves:
- 3+ years of experience in deployment engineering, delivering production AI integrations and automation workflows.
- Deep, hands-on experience with LLM-based systems — including prompting, tool use, RAG/knowledge retrieval, evaluation, and handling failure modes.
- Proven ability to translate complex business processes into robust, testable AI-driven workflows.
- Experience implementing third-party integrations (APIs, webhooks) and authentication patterns (OAuth, API keys, data formats).
- Strong coding skills to implement features and glue code with proper testing, monitoring, and logging.
- Cloud fundamentals: deployments, observability, and production debugging.
- Pragmatic, ownership-driven mindset — you ship fast, iterate, and take responsibility for outcomes.
Nice to have:
- TypeScript or Python experience.
- Experience with n8n or similar workflow automation tooling.
- Familiarity with voice/telephony integrations.
- SQL proficiency.
- Monitoring/tracing tooling experience.
- GDPR / Privacy-by-Design awareness.
COMPENSATION & BENEFITS
- Salary: €60,000 – €90,000 per year, depending on experience.
- Fully remote role within Germany.
- Work within a high-velocity, small team with significant ownership and direct impact on the product.
Please note: Visa sponsorship is not available for this role.
LOCATION
Fully remote — based in Germany. You'll collaborate closely with a team spanning Germany and Austria.
What you'll do
- Act as the technical bridge between product and customer setups — translating business requirements into robust, production-ready implementations.
- Lead end-to-end rollouts of AI assistant configurations in production, including workflows, logic, data flows, prompts, and guardrails.
- Implement integrations with third-party systems via APIs and webhooks, covering CRMs, calendars, ticketing, payments, and common auth patterns (OAuth, API keys).
- Develop glue code and small-to-medium features with tests, monitoring, and logging to map customer use cases to production systems.
- Debug live issues across calls, flows, and data pipelines — and ship rapid fixes under production conditions.
- Build reusable templates, deployment playbooks, and best practices to make setups scalable and repeatable across customers.
- Maintain a tight feedback loop with product and engineering by surfacing pain points, feature gaps, and recurring patterns with concrete recommendations.
- Own deployment success and ensure customer setups function reliably in live production call environments.
What they require
- 3+ years of experience in deployment engineering, delivering production AI integrations and automation workflows.
- Deep, hands-on experience with LLM-based systems — including prompting, tool use, RAG/knowledge retrieval, evaluation, and handling failure modes.
- Proven ability to translate complex business processes into robust, testable AI-driven workflows.
- Experience implementing third-party integrations (APIs, webhooks) and authentication patterns (OAuth, API keys, data formats).
- Strong coding skills to implement features and glue code with proper testing, monitoring, and logging.
- Cloud fundamentals: deployments, observability, and production debugging.
- Pragmatic, ownership-driven mindset — you ship fast, iterate, and take responsibility for outcomes.
Benefits
- Salary: €60,000 – €90,000 per year, depending on experience.
- Fully remote role within Germany.
- Work within a high-velocity, small team with significant ownership and direct impact on the product.
A fast-growing fintech startup building modern banking infrastructure for global businesses and AI-powered financial operations.