Manager, Forward Deployed Engineering

About Parloa

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.

About the role:

As a Manager, Forward Deployed Engineering 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.

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.

Areas of ownership:

• Lead and develop the team: hire, coach, and grow a team of FDEs; set clear expectations; run 1:1s, feedback cycles, and performance development.
• Own capacity planning and staffing: allocate engineers across parallel strategic projects, manage load and utilization, and anticipate delivery bottlenecks early.
• Drive project delivery management: own engineering delivery across deployments — milestones, dependencies, risk management, escalation paths, and stakeholder alignment.
• Establish time tracking and delivery visibility: implement lightweight tracking and reporting that creates trusted insight into effort, progress, and capacity (without bureaucracy).
• Provide technical leadership and escalation support: guide architecture and implementation choices, review designs/code when needed, and unblock high-severity issues in production environments.
• Create scalable field engineering practices: build reusable patterns, playbooks, and standards that improve reliability, maintainability, and speed across deployments.
• Shape the product via field learnings: translate recurring customer needs into clear productization proposals and partner with Product/Core Engineering to reduce one-offs over time.
• Partner with customer engineering and enterprise stakeholders: collaborate directly with customer teams (architecture, security, platform) to deliver outcomes and build long-term technical trust.

Our Tech Stack: 

Typescript, NodeJS, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:

• Experience level: 8+ years in software engineering, systems integration, DevOps, or data engineering roles with meaningful production responsibility.
• People leadership: proven ability to lead and develop engineers (e.g., formal management, team lead responsibility, coaching, hiring, performance growth).
• Enterprise delivery track record: demonstrated success delivering complex technical projects in large enterprise environments with multiple stakeholders and constraints.
• Technical breadth and depth: strong capabilities across backend engineering, APIs, cloud platforms, Kubernetes, infrastructure-as-code, and databases — able to review designs and guide production decisions.
• Hands-on effectiveness: able to personally own and drive smaller technical workstreams end-to-end and to jump into debugging/implementation when necessary.
• Operational excellence: strong planning, prioritization, capacity thinking, and risk management; creates delivery clarity without unnecessary process overhead.
• Customer-facing communication: confident and credible with customer engineering teams and senior technical stakeholders; clear written and verbal communication.
• 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.

Our Recruiting Process:

Talent Acquisition → Hiring Manager → Technical Interview(s) → Bar Raiser

Why Parloa?

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 customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale and want your work to matter in real, everyday moments, this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Parloa is committed to upholding the highest data protection standards for our clients' and employees' data. All our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information.

Parloa is an e-verify employer in the USA. Please click here to learn more.

* We provide equal opportunities to all qualified applicants regardless race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background and other characteristics.