Forward Deployed Engineer (fde) Consultant

This role focuses on leading the design, build, and deployment of cybersecurity and artificial intelligence-enabled solutions for clients. It involves guiding engineering teams, supporting pursuits with demos and prototypes, and managing delivery quality. The role requires experience in full-stack development and specifically building/deploying generative AI or LLM solutions in production environments.

What you'd actually do

  1. Leading the design, build, and deployment of cybersecurity and artificial intelligence-enabled solutions aligned to client requirements and target architecture
  2. Guiding engineering teams through technical decisions, troubleshooting, code reviews, and delivery execution across client engagements
  3. Supporting pursuits through demos, proofs of concept, prototypes, solution design, effort estimates, and pricing inputs
  4. Managing delivery quality, scope, timelines, and client expectations while addressing escalations and protecting engagement outcomes
  5. Capturing reusable delivery learnings, documentation, and runbooks to strengthen delivery practices and client enablement

Skills

Required

  • full stack development
  • front-end technologies
  • back-end technologies
  • generative artificial intelligence
  • large language model solutions
  • JavaScript
  • TypeScript
  • HTML5
  • CSS3
  • modern front-end framework
  • Node.js
  • Python
  • Java
  • relational databases
  • NoSQL databases
  • REST application programming interfaces
  • microservices
  • serverless architectures
  • Amazon Web Services
  • Microsoft Azure
  • Google Cloud Platform
  • code reviews
  • technical solutioning
  • demos
  • proofs of concept
  • prototypes
  • effort estimates
  • client requirements translation
  • scalable technical solutions

Nice to have

  • cybersecurity concepts
  • application security
  • cloud security
  • identity
  • detection engineering
  • DevSecOps practices
  • secure software development life cycle
  • Elasticsearch
  • OpenSearch
  • Neo4j
  • Kubernetes
  • GitOps
  • cloud-native design patterns
  • Amazon Web Services certifications
  • Microsoft Azure certifications
  • Google Cloud Platform certifications
  • TensorFlow
  • PyTorch

What the JD emphasized

  • building and deploying generative artificial intelligence or large language model solutions in client or production environments

Other signals

  • client delivery
  • production environments
  • generative artificial intelligence
  • large language model solutions