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Parloa is building agentic AI for enterprise customer experience, having powered over one billion interactions for companies like Booking.com, HealthEquity, Allianz, SAP, and TUI. As a Staff Product Engineer, you will work directly embedded within strategic enterprise customers, building production-grade software that enables their AI agents to operate at scale.
Your primary responsibility is to bridge the gap between Parloa's AMP platform and each customer's unique systems and requirements. You will handle the integrations, capabilities, and architectural decisions that the platform does not yet cover—whether that's systems of record, telephony integrations, state management, data readiness, multi-agent orchestration, or retrieval systems. You will own the hardest engagements: complex multi-workstream programmes where pilot-grade solutions would fail in production, and novel capabilities that Parloa has never built before.
You will work alongside Deployment Strategists (who define success) as the technical leadership for accounts, owning architecture and build decisions. On some accounts, you will own the engineering independently. Your scope includes leading complex programmes with multiple workstreams, making architecture decisions that span Parloa's platform and customer organizations, ensuring production quality and security at enterprise scale (including PII handling, access control, audit trails, and regulated-industry compliance), debugging live issues both technical and model-driven, growing accounts into new use cases and renewals, mentoring other Product Engineers, and representing Parloa with senior customer technical stakeholders (principal engineers, architects, security leaders).
This is not a platform engineering role, not agent configuration work, and not a people-management position. You will write and review code every week as an individual contributor. You will travel up to 25% to customer sites depending on engagements.
Tech stack includes Go, TypeScript, Node.js, Python, FastAPI, frontier LLMs, MCP, Azure, Kubernetes, Docker, Terraform, MongoDB, Redis, and Kafka/NATS—though most engagements add something new.
REQUIREMENTS:
- 8+ years of professional software development, delivering production systems end to end. Fluent in TypeScript or Python, or able to get there quickly.
- 5+ years leading the design and architecture of large-scale production systems in customer-facing or enterprise environments, with focus on reliability, scale, and failure modes.
- Experience leading agentic, spec-driven development in production. You know when a coding agent's output is wrong and what checks it needs before shipping.
- Track record in long-term accounts or fast experiments. You have owned a strategic enterprise relationship over several years through expansion, renewal, or leadership change, or tested new ideas at the frontier and decided quickly whether they were worth building.
- Experience as a mentor or tech lead, helping engineers become independent.
- Comfortable with ambiguity and with customers. You work well in complex organizations, build trust quickly with new customer teams, spot risks early, and keep judgment when stakes are high.
- Willingness to travel up to 25% to customer sites.
- Strong spoken and written communication skills in English.
NICE TO HAVE:
- Experience building or deploying an LLM-powered system used by real users in production.
- Hands-on experience with eval frameworks, agent tooling, RAG, prompt engineering, or multi-agent orchestration.
- Founder or founding-engineer background.
- Forward-deployed, solutions engineering, product engineering, or strategic-partner experience at an enterprise software or AI company.
- Voice or conversational AI, or contact center, telephony, or CCaaS integration experience.
- Experience in regulated industries such as banking, insurance, or telecom.
