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Parloa is an agentic AI platform that powers enterprise customer experience at scale, having processed over one billion customer interactions for companies like Booking.com, SAP, and Allianz. The company is building AI systems that understand, reason, and take action in customer support contexts.
As Manager of Forward Deployed Engineering, you will lead a high-impact team of field engineers (FDEs) responsible for delivering Parloa's most strategic enterprise deployments. FDEs are in-field engineers who build custom solutions, adapt architecture to enterprise constraints, and engineer integrations across complex systems to ensure successful deployments.
Key responsibilities include:
• Team Leadership: Hire, coach, and develop FDEs; establish clear expectations; conduct 1:1s, feedback cycles, and performance development.
• Capacity & Staffing: Allocate engineers across parallel strategic projects, manage utilization, and anticipate delivery bottlenecks.
• Delivery Management: Own engineering delivery across deployments—milestones, dependencies, risk management, escalation, and stakeholder alignment.
• Visibility & Tracking: Implement lightweight time tracking and reporting that provides trusted insight into effort, progress, and capacity without bureaucratic overhead.
• Technical Leadership: Guide architecture and implementation decisions, review designs and code, and unblock high-severity production issues.
• Field Engineering Practices: Build reusable patterns, playbooks, and standards that improve reliability, maintainability, and speed across deployments.
• Product Feedback: Translate recurring customer needs into productization proposals and partner with Product/Core Engineering to reduce one-offs.
• Customer Partnerships: Collaborate directly with customer engineering teams (architecture, security, platform) to deliver outcomes and build technical trust.
You will work with a modern tech stack including TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, and MCP.
Ideal candidates have 8+ years in software engineering, systems integration, DevOps, or data engineering with proven people leadership experience (formal management, team lead roles, hiring, coaching). You should have a track record delivering complex technical projects in large enterprise environments, strong technical breadth across backend engineering, APIs, cloud platforms, Kubernetes, infrastructure-as-code, and databases. Hands-on effectiveness is essential—you can personally own and drive technical workstreams and jump into debugging when needed. Experience building or integrating AI/LLM-powered systems (agent workflows, orchestration, evaluation, vector databases, guardrails) in forward-deployed or solutions engineering environments is a strong plus.
