Forward Deployed Engineers

il y a 2 semaines

Paris, Île-de-France Photon Group Temps plein
Description

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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