Maki

AI Deployment Architect

Paris
USD 75k - 85k
AI Machine Learning SQL LLM
Description

Forward Deployed Engineer - Paris

Department: Implementation

Location: Paris

Compensation: €75K – €85K • Offers Equity

Employment Type: FullTime

We are hiring Forward Deployed Engineers to configure, deploy, and evolve our agents for enterprise customers. This role sits at the intersection of product, engineering, and customer delivery ; you will translate business requirements into robust configurations, ensure each deployment reflects client needs, and iterate rapidly to maintain high performance and system stability.

You will be a primary technical partner to our customers, guiding them through configuration decisions, troubleshooting complex behaviors, and shaping how they design and operationalize AI-driven screening. You will also act as a critical feedback conduit between the field and the product team, surfacing patterns that should be platformized and validating new capabilities with real-world customers.

This is a highly technical & hands-on role. As deployments accelerate across industries and geographies, you will help define the standards, tools, and best practices that make our agents scalable.

What you will do

Configuration and deployment

  • Build and adapt screening flows based on customer jobs and requirements.

  • Configure state prompts, tone parameters, voice selection, transitions, and conditional logic.

  • Set up and maintain custom vocabularies for ASR when relevant.

  • Prepare and run demos; support pilot implementations from start to finish.

Troubleshooting and iteration

  • Analyze conversation transcripts and identify sources of errors or drift.

  • Run isolated state tests for targeted debugging.

  • Iterate rapidly on prompts and configurations to improve performance.

  • Use SQL to investigate behavioral patterns, identify systemic issues, and validate improvements.

Client partnership

  • Advise customers on screening design, personas, and best practices for AI-driven interviews.

  • Communicate technical concepts, limitations, and trade-offs clearly.

  • Manage expectations during pilots; build structured feedback loops that drive continuous improvement.

  • Act as a trusted guide throughout deployment and iteration cycles.

Product collaboration

  • Surface recurring field issues that should become productized solutions.

  • Contribute insights that shape new configuration surfaces, evaluation tools, and system-level capabilities.

  • Partner with product and engineering teams to test new features with selected customers and validate readiness for scale.

What makes this role unique

  • You sit closest to real-world usage; your insights will directly shape how our agents evolve.

  • You bridge product and customer needs, ensuring enterprise deployments remain robust, predictable, and high performing.

  • You influence how AI-driven hiring is operationalized across the world’s leading companies.

  • You will help define repeatable playbooks, tools, and standards that allow the deployment function to scale.

  • As the first hire fully dedicated to this function, you will shape the boundaries of the role itself and set the industry bar for what excellence looks like in full-deployment engineering for conversational AI.

Preferred experience

Experience

  • Graduated from top engineering school or business/engineering dual-degree

  • Prior client-facing technical experience, ideally supporting enterprise implementations.

Technical skills

  • Hands-on work with conversational AI, LLM prompting, applied ML models, or workflow-based configuration.

  • Ability to debug state logic, model outputs, and configuration inconsistencies.

  • SQL proficiency for analytics and performance investigation.

  • Comfort with light scripting and structured configuration formats.

Analytical and product mindset

  • Strong ability to reason about system constraints and edge cases.

  • Ability to distinguish between local configuration work and product-level feature needs.

  • Structured approach to experimentation and iteration.

Client-facing abilities

  • Clear and concise communication with both technical and non-technical stakeholders.

  • Ability to present, educate, and manage expectations during pilots and demos.

  • Confidence in advising customers and steering conversations.

Recruitment process

  • Stage 1 - Screening call with our agent (15 min)

  • Stage 2 - COO interview (45 min)

  • Stage 2 - Implementation lead interview (45 min)

  • Stage 3 - Deep-dive technical interview (60 min)

  • Stage 4 - Founder interview (45 min)

  • Stage 5 - Offer and alignment discussion

Maki
Maki

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