Forward Deployed Engineer (FDE 3)

ProdaptIrving, TX
2d

About The Position

Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. Focus: Architecture, Cloud Deployment, LLMOps & Reliability Role Summary: As a Lead FDEs you move from ‘working prototypes’ to scalable, secure, observable, and production-ready systems. You design microservices, deploy workloads in cloud environments, implement evaluation pipelines and guardrails, and bring engineering discipline across reliability, testing, and architecture.

Requirements

  • DevOps: Deep knowledge of Docker, K8s, CI/CD pipelines, and IaC (Terraform).
  • Architecture: Microservices patterns, TDD (Test Driven Development), Database design (SQL & NoSQL).
  • AI/ML: Advanced RAG techniques (Hybrid Search, Re-ranking), building evaluation loops, managing Guardrails.
  • Frameworks: Expert-level FastAPI and Next.js/Remix.
  • Security: IAM, OAuth2, network policies.
  • Observability: Prometheus, Grafana, OpenTelemetry.
  • Ability to communicate trade-offs and architecture decisions clearly.
  • Leadership in guiding Junior FDEs and cross-functional teams.
  • Strong problem‑solving mindset and scenario analysis.
  • Ability to translate business needs into technical specifications.
  • Reliability mindset with ownership for delivery and stability.

Responsibilities

  • Cloud & DevOps: Containerize applications using Docker Compose/Kubernetes and automate cloud deployments (AWS/Azure) using Terraform.
  • Advanced Backend Architecture: Design microservices (MSA) with Clean Architecture principles. Implement Model Context Protocol (MCP) servers and clients.
  • LLMOps & Evaluation: Implement evaluation frameworks (RAGAS, BLEU) to empirically test RAG performance. Build pipelines that monitor model hallucinations and quality.
  • Observability: logs, metrics, traces, SLOs.
  • Client Communication: Define technical requirements based on business needs and explain technical trade-offs to non-technical stakeholders.
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