Lead High-Impact Deployments
Design and deliver secure, scalable post-sales implementations for commercial customers—across AWS, GCP, and Azure
Guide customers through architecture, integration, optimization, and tuning—especially around AI/LLM and RAG use cases
Create reference architectures, onboarding guides, and playbooks that reduce time-to-value and accelerate adoption
Run enablement sessions, whiteboarding workshops, and POCs to maximize customer value and foster long-term partnerships
Solve complex infrastructure and data pipeline issues—ensuring stability, observability, and high performance
Feed customer insights directly to Product & Engineering to shape our roadmap and improve enterprise capabilities

5+ years of experience in post-sales engineering, solutions architecture, or technical consulting
Deep experience with cloud-native architectures (AWS, Azure, GCP), containers (Docker, Kubernetes), and IaC tools
Strong hands-on Python skills for scripting, API integration, and automation
Proven success leading enterprise-scale deployments and solving real customer problems with technical precision
Excellent communicator—you simplify the complex and build trust across both engineering and business audiences
Comfort navigating ambiguity and speed—especially in startup or high-growth environments
Willing to travel up to 20%

Bonus Points

Experience delivering or optimizing RAG pipelines, vector databases, or LLM-based applications
Knowledge of DevSecOps best practices and commercial security/compliance frameworks (SOC 2, ISO 27001)
Familiarity with both pre-sales and post-sales solutioning across AI/ML workflows
Startup DNA
you move fast, stay scrappy, and take ownership end-to-end

Strong Benefits: Competitive salary, full health benefits, equity, and parental leave

Forward Deployed Engineer

Key skills