Forward Deployed Engineer

🕒 il y a 28 jours

🌐 Royaume-Uni, Irlande – Distant

infoinfo

⏰ Temps Plein

🟢 Junior

🟡 Intermédiaire

👷🏻‍♀️ Ingénieur

🚫👨‍🎓 Aucun diplôme requis

👻 Score fantôme 14%

infoinfo

🗣️🇺🇸🇬🇧 Anglais requis

Airflow

BigQuery

Kafka

Python

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Kinaxis

1001 - 5000 employés

💼 Conseil

🏥 Santé

🏭 Fabrication

💰 €33 000 000 Venture Round en 2000-05

Consulting • Healthcare • Manufacturing

Kinaxis est un fournisseur de premier plan de solutions d'orchestration de chaîne logistique, spécialisé dans la planification et la gestion de chaîne logistique enrichies par l'intelligence artificielle. Leur plateforme phare, Maestro, permet aux organisations de maîtriser la complexité et d'optimiser les processus décisionnels sur l'ensemble de la chaîne logistique. En intégrant des analyses avancées à une visibilité des données en temps réel, Kinaxis aide les entreprises à améliorer leur efficacité opérationnelle, prédire la demande, et réagir de manière proactive aux perturbations.

Description

• Own customer solutions end-to-end • Rapidly prototype, iterate, and deploy solutions in live operational environments • Build trusted relationships from individual contributors to executive sponsors • Serve as the technical face of Kinaxis with customers • Manage multiple customer engagements in parallel according to customer priorities and pod capacity • Set expectations, renegotiate when conditions change, operate independently, and own outcomes • Operate in a small, multidisciplinary, self-directed POD team • Partner with Product and Engineering to turn field learnings into durable platform capabilities • Drive adoption and guide customers through solution transitions • Mentor customer operators and help teams adopt new ways of working • Measure success through business outcomes such as efficiency gains, exception reduction, and SLA improvements • Bring field learnings back into the Kinaxis Maestro Platform and abstract successful solutions into reusable patterns

🎯 Exigences

• 2–5 years of professional experience in software engineering, data engineering, solutions engineering, or a technical-founder role • Hands-on experience building LLM-based applications, RAG systems, multi-agent workflows, tool-use patterns, prompt and context engineering • Familiarity with AI-assisted development tools such as Copilot, Claude Code, and agentic IDE workflows • Understanding of agentic orchestration patterns, including single versus multi-agent architectures and handling memory and state • Solid software engineering fundamentals and experience building and shipping real systems • Proficiency in at least one backend language; Python strongly preferred • Ability to read and contribute across a polyglot codebase • Experience with REST and streaming APIs, authentication patterns, and enterprise-system integration • Ability to build and maintain data pipelines for ingestion, transformation, serving, and monitoring using Airflow, Kafka, dbt, or equivalents • Working familiarity with modern data platforms such as Snowflake, Databricks, BigQuery, or similar • Knowledge of data modeling and performance fundamentals • Strong debugging ability with imperfect, real-world data in production environments • Ability to travel as required, up to 50% • Prior customer-facing technical experience is a strong signal, though not a requirement • Supply chain planning, logistics, or operations exposure is a plus, not a requirement

🏖️ Avantages

• Flexible vacation and Kinaxis Days (company-wide days off) • Flexible work options • Physical and mental well-being programs • Regularly scheduled virtual fitness classes • Mentorship programs, training, and career development • Recognition programs and referral rewards • Hackathons • Workplace accommodations upon request for candidates with specific needs or disabilities

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