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parloa
<h2><strong>About Parloa</strong></h2> <p>Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.</p> <h2><strong>About the role:</strong></h2> <p>As a <strong>Manager, Forward Deployed Engineering </strong>at Parloa, you’ll be on the front lines of enterprise AI adoption — leading a high-impact team of FDEs that delivers our most strategic enterprise deployments. Your mission is to ensure our consistent deployment excellence: predictable delivery, strong engineering quality, and fast unblocking in complex enterprise environments — while staying technically credible yourself.</p> <p>FDEs are our in-field engineers. They build what doesn’t exist yet, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. As a Manager, you make that work repeatable and reliable across multiple customer projects — through strong delivery leadership, clear priorities, and hands-on technical guidance.</p> <h2><strong>Areas of ownership:</strong></h2> <ul> <li><strong>Lead and develop the team:</strong> hire, coach, and grow a team of FDEs; set clear expectations; run 1:1s, feedback cycles, and performance development.</li> <li><strong>Own capacity planning and staffing:</strong> allocate engineers across parallel strategic projects, manage load and utilization, and anticipate delivery bottlenecks early.</li> <li><strong>Drive project delivery management:</strong> own engineering delivery across deployments — milestones, dependencies, risk management, escalation paths, and stakeholder alignment.</li> <li><strong>Establish time tracking and delivery visibility:</strong> implement lightweight tracking and reporting that creates trusted insight into effort, progress, and capacity (without bureaucracy).</li> <li><strong>Provide technical leadership and escalation support:</strong> guide architecture and implementation choices, review designs/code when needed, and unblock high-severity issues in production environments.</li> <li><strong>Create scalable field engineering practices:</strong> build reusable patterns, playbooks, and standards that improve reliability, maintainability, and speed across deployments.</li> <li><strong>Shape the product via field learnings: </strong>translate recurring customer needs into clear productization proposals and partner with Product/Core Engineering to reduce one-offs over time.</li> <li><strong>Partner with customer engineering and enterprise stakeholders:</strong> collaborate directly with customer teams (architecture, security, platform) to deliver outcomes and build long-term technical trust.</li> </ul> <h3><strong>Our Tech Stack: </strong></h3> <p>Typescript, NodeJS, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP</p> <h2><strong>Who you are:</strong></h2> <ul> <li><strong>Experience level:</strong> 8+ years in software engineering, systems integration, DevOps, or data engineering roles with meaningful production responsibility.</li> <li><strong>People leadership:</strong> proven ability to lead and develop engineers (e.g., formal management, team lead responsibility, coaching, hiring, performance growth).</li> <li><strong>Enterprise delivery track record:</strong> demonstrated success delivering complex technical projects in large enterprise environments with multiple stakeholders and constraints.</li> <li><strong>Technical breadth and depth:</strong> strong capabilities across backend engineering, APIs, cloud platforms, Kubernetes, infrastructure-as-code, and databases — able to review designs and guide production decisions.</li> <li><strong>Hands-on effectiveness:</strong> able to personally own and drive smaller technical workstreams end-to-end and to jump into debugging/implementation when necessary.</li> <li><strong>Operational excellence:</strong> strong planning, prioritization, capacity thinking, and risk management; creates delivery clarity without unnecessary process overhead.</li> <li><strong>Customer-facing communication:</strong> confident and credible with customer engineering teams and senior technical stakeholders; clear written and verbal communication.</li> <li><strong>Strong plus: experience building or integrating AI/LLM-powered systems (agent workflows, orchestration, evaluation, vector DBs, guardrails), ideally in forward-deployed or solutions engineering environments.</strong></li> </ul> <h2><strong>Our Recruiting Process:</strong></h2> <div> <p>Talent Acquisition → Hiring Manager → Technical Interview(s) → Bar Raiser<br><br></p> <h2><strong>Why Parloa?</strong></h2> <p>We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important custom