Cloud Engineer - AWS [Founding]

We’re looking for a founding AWS DevSecOps engineer who will act as the primary architect and builder of our entire technology foundation. This is a true Greenfield opportunity, no legacy systems, no constraints, no existing infra. You will design and build everything from scratch for an AI-driven product at the intersection of MarTech and advanced data systems. This role is for someone who thrives in ambiguity, takes ownership, and can bridge cloud infrastructure, data pipelines, and AI systems into one cohesive platform.

What You’ll Own

• Architect and deploy scalable, secure AWS infrastructure (EC2, S3, RDS, Lambda, VPC, IAM)
• Design and build the end-to-end data layer (ingestion → processing → storage → usage)
• Build 0→1 systems from scratch, making foundational architectural decisions
• Translate high-level product ideas into working systems, data flows, and infrastructure
• Work across product, data, and AI teams to ensure systems are integrated, not siloed
• Build and automate CI/CD, internal tooling, and AI-enabled workflows
• Enable and support AI/ML systems in production, including data pipelines and infra
• Make independent technical decisions in an environment with evolving requirements
• Continuously improve systems based on real usage, scale, and constraints — not theory
• Contribute to AI agents, prompt workflows, and product-level automation use cases

What We’re Looking For AWS & System Design

• 5+ years of hands-on experience building on AWS
• Strong understanding of distributed systems and scalable architecture
• Ability to translate ambiguous requirements into clear technical systems
• AWS Certification (Solutions Architect / DevOps Engineer) is required 0 → 1 Ownership
• Proven experience building production systems from scratch
• Comfortable operating with high ownership and low structure
• Strong decision-making ability under uncertainty and evolving requirements Infrastructure & Data Engineering
• Strong experience with Infrastructure as Code (Terraform required)
• Experience designing and building data pipelines and data flows
• Hands-on with high-volume systems, storage layers, and data processing AI & Modern Cloud Stack
• Experience working with or supporting AI/ML systems in production
• Familiarity with RAG architectures, vector databases (OpenSearch, Pinecone, etc.)
• Strong understanding of containerized environments (EKS/ECS, Docker) Observability & Reliability
• Experience implementing monitoring using CloudWatch, Prometheus, Grafana
• Strong understanding of performance optimization, scaling, and system reliability This is a role for someone who wants to build something from zero, not optimize what already exists.