15 meilleures offres (lead cloud & data engineer gcp, paris, a8) (à pourvoir)

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Photon —Paris (75)
- Azure
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- JavaScript
Senior tech lead AI engineering - Delivery
Ekimetrics —Paris (75)
- Temps plein
- Azure
- AWS
- Intelligence artificielle
Staff Engineer - Endpoint security
GitGuardian —Paris (75)
- Télétravail partiel
- Azure
- Anglais
- JavaScript
HealthHub Signalling Integrator (M/F/X)
ALSTOM —Saint-Ouen (93)
- Temps plein
- Informatique
- Azure
- DevOps
Team Lead, Platform Services
Owkin —Paris (75)
- Temps plein
- Télétravail partiel
- Azure
- Anglais
- Intelligence artificielle
Postuler rapidement
Security Analyst
Vestiaire Collective —Paris (75)
- Télétravail partiel
- Master
- SQL
- Niveau Licence
Postuler rapidement
il y a 9 jours
Senior CyberSecurity Researcher, Paris
GitGuardian —Paris (75)
- Télétravail partiel
- Azure
- Anglais
- Scripting
Chef de Projet Data F/H
Viseo —Boulogne-Billancourt (92)
- Temps plein
- Azure
- SQL
Senior Sales Engineer - Data & AI Security
Veeam Software —Paris (75)
- Temps plein
- Télétravail
- Azure
- AWS
- Linux
ALTERNANCE - Assistant.e Chef de Projet Data
Moët Hennessy —Paris (75)
- Temps plein
- Anglais
- Master
- SQL
Senior Backend Engineer Java / AI (H/F)
ALTEN —Boulogne-Billancourt (92)
- Temps plein
- Azure
- DevOps
- Ingénierie
Postuler rapidement
Senior Staff Customer Engineer – Automotive AI
Sonatus —Paris (75)
- Télétravail
- Azure
- Niveau Doctorat
- Master
Postuler rapidement
Customer Success Manager
Scality —Paris (75)
- Temps plein
- Logiciels de GRC/CRM
- Espagnol
- Azure
Engineering Manager - Observability & Reliability Engineering Obsession (x/f/m)
Doctolib —Levallois-Perret (92)
- Temps plein
- Java
- Leadership
- Python
Postuler rapidement
Lakebase Sales Specialist
Databricks —Paris (75)
- Azure
- Bases de données
- Niveau Licence
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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : lead cloud & data engineer gcp (paris, a8)

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Forward Deployed Engineers - Python - Paris

Photon -
Paris (75)

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Détails de l'emploi

Qualifications

TensorFlow
CI/CD
Azure
Kubernetes
Ansible
PyTorch
DevOps
Chiffrement
Google Cloud Platform
Docker
JavaScript
Systèmes distribués
Terraform
Ingénierie système
Securité
Production
SaaS
TypeScript
Python
Debugging

Description complète du poste

Key Responsibilities

1. Deployment Engineering

Lead the end-to-end technical implementation of the Agentic platform in enterprise environments.
Design and build robust integration pipelines , connecting customer data sources, APIs, and systems of record to the platform.
Deploy and scale machine learning models in production, ensuring performance, reliability, and monitoring.
Automate deployments using CI/CD pipelines, infrastructure-as-code, and container orchestration (Docker, Kubernetes).

2. AI Platform Integration & Optimization

Implement custom extensions, SDKs, and APIs to adapt the platform to customer-specific use cases.
Build tools, scripts, and microservices to handle data preprocessing, feature engineering, and real-time inference .
Optimize model serving, caching, and resource allocation for low-latency, high-throughput environments.

3. Reliability, Security & Compliance

Architect solutions that meet enterprise-grade standards for resilience, observability, and scalability.
Ensure deployments adhere to security best practices (encryption, identity management, network security).
Navigate compliance requirements such as SOC2, HIPAA, GDPR , and customer-specific regulatory constraints.

4. Engineering Leadership & Technical Escalation

Serve as the senior technical lead on customer deployments, resolving complex engineering challenges.
Partner closely with customer engineering teams to embed the platform into production workflows.
Provide critical field feedback to product and core engineering teams on performance, scaling, and enterprise integration needs.

5. Enablement & Knowledge Sharing

Create reusable deployment templates, automation scripts, and playbooks to accelerate future projects.
Mentor other Forward Deploy Engineers on advanced deployment patterns, DevOps practices, and ML systems engineering.

Qualifications

Engineering Expertise
- 10+ years in software engineering, infrastructure engineering, or applied ML engineering.
- Strong proficiency in Python , TypeScript/JavaScript , or other backend languages.
- Experience deploying systems on cloud platforms (AWS, GCP, Azure) using Kubernetes and serverless frameworks.
- Deep understanding of API design, distributed systems, and data engineering workflows .
- Hands-on experience operationalizing ML models in production (TensorFlow, PyTorch, Hugging Face, or custom inference engines).
DevOps & Infrastructure
- Strong background in CI/CD pipelines, infrastructure as code (Terraform, Helm, Ansible) .
- Skilled in setting up monitoring, observability, and alerting (Prometheus, Grafana, ELK, Datadog).
- Familiarity with performance profiling, scaling strategies, and SRE principles.
Security & Compliance Awareness
- Knowledge of enterprise SaaS security models (SSO, RBAC, encryption, API security).
- Experience working in environments subject to compliance frameworks (SOC2, HIPAA, GDPR).
Soft Skills
- Excellent debugging and problem-solving in high-pressure deployment environments .
- Strong communication with technical stakeholders (engineering teams, architects, CTOs).
- Comfort working in fast-moving, ambiguous situations with minimal guidance.

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : lead cloud & data engineer gcp (paris, a8)

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