AI Systems Architect Lead

Devleaps

Hoofddorp

Hybrid

EUR 120,000 - 160,000

Full time

21 hours ago
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Job summary

Devleaps is seeking an AI Tech Lead to set the architecture for reliable AI capabilities embedded in client systems. You will define model serving, retrieval, orchestration, and platform services, while enforcing guardrails and monitoring.

You will work with client teams to elevate production AI features and ensure robust, scalable solutions. You will drive evaluation pipelines, cost modeling, and latency budgets with the rigor of a production system, designing for graceful degradation and clear

Qualifications

  • 6–10+ years of software engineering with lead/principal experience.

Responsibilities

  • Lead technical direction on AI engagements: architecture of AI estate and platform services.
  • Build and enforce guardrails: input/output filtering, content policies, audit logging, human-in-the-loop checks.
  • Embed as a technical anchor in client teams: pair with engineers on production AI features and review work to a common standard.
  • Own evaluation and observability as architecture: pipelines, drift detection, cost per inference, latency budgets.
  • Design for failure: fallback behaviour, rate limiting, circuit breaking for AI features.
  • Translate AI capabilities into CTO-facing decisions, clarifying what is possible with current data.
  • Identify bottlenecks and remove work that slows teams down.

Skills

Architectural leadership
Lead engineering
LLM/ML systems
Python
AI tooling
Cloud platforms (Azure)
MLOps
API design
Stakeholder management

Tools

LangChain
LangGraph
LlamaIndex
OpenAI APIs
Anthropic
Azure OpenAI
Bedrock

Job description

Devleaps is seeking an AI Tech Lead to set the architecture for reliable AI capabilities embedded in client systems. You will define model serving, retrieval, orchestration, and platform services, while enforcing guardrails and monitoring.

You will work with client teams to elevate production AI features and ensure robust, scalable solutions. You will drive evaluation pipelines, cost modeling, and latency budgets with the rigor of a production system, designing for graceful degradation and clear

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