Forward Deployed Engineer

Overview

As a Forward Deployed Engineer, you embedded with customer operations to identify where AI delivers genuine impact and ship it in production. You will own the end-to-end delivery—from discovery through to deployed features—across front-end, back-end, data pipelines, and AI services. You operate at high autonomy, communicating with both technical and non-technical stakeholders, and you shape the roadmap with field learnings. This role offers hands-on ownership of AI-backed workflows in enterprise contexts, with rapid cycles and direct customer impact.

Responsibilities

• Embed with customer teams to understand real operations, data, constraints, and people
• Lead technical discovery to separate root bottlenecks from symptoms
• Design and ship full-lifecycle features across front-end and back-end, including APIs and event-driven services
• Leverage platform and AI service catalogues to reuse or extend existing capabilities
• Own requirements gathering when necessary and collaborate with owning teams to scope and implement
• Work on data pipelines, model serving, retrieval and evaluation for AI features
• Ship a working first version quickly and then harden it with monitoring and production-grade reliability
• Communicate trade-offs to product owners and architects, turning field insights into roadmap input

Key requirements

• 5+ years building and operating production systems
• Proficiency in at least one modern language (Python preferred)
• Cloud and Kubernetes experience in building and operating cloud-native services
• Experience with AI/LLM integration in production (model APIs, gateways, observability)
• Hands-on with agentic systems and orchestration frameworks
• Experience with retrieval and RAG (embeddings, vector stores, indexing)
• REST APIs, data contracts, authentication/authorization, and enterprise integration
• Deployment and IaC skills (Docker, Kubernetes, Helm, GitOps/ArgoCD, Terraform)
• Data handling across relational, document, vector, and object stores
• Understanding of event-driven, distributed systems and AI failure modes
• Familiarity with agentic tooling in daily engineering work
• ambition and speed in ambiguous environments
• clear communication with diverse stakeholders
• pragmatic problem-solving
• Python
• cloud-native design
• Azure (AKS, Blob Storage, Key Vault, Azure AI services)

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