AWS DevSecOps [Founding]

We’re looking for a founding AWS DevSecOps engineer to act as the primary architect and builder of our technology foundation.

This is a true Greenfield opportunity, no legacy systems, no existing infrastructure, no technical debt. You will design and deploy the entire AWS ecosystem from scratch for an advanced AI-Tech and MarTech product.

This role is for someone who thrives in ambiguity and can bridge infrastructure, data systems, security, and AI into one cohesive platform.

What You’ll Own

• Architect and deploy secure, scalable AWS infrastructure (EC2, S3, RDS, Lambda, VPC, IAM)

• Design and implement the end-to-end data layer (ingestion → transformation → storage → usage)

• Build 0→1 infrastructure and systems from scratch, making foundational architecture decisions

• Translate high-level product direction into working systems, data flows, and infrastructure

• Work across product, data, and AI teams to ensure tightly integrated systems

• Build and automate CI/CD pipelines, internal tools, and AI-enabled workflows

• Enable and support AI/ML systems in production, including data pipelines and inference workflows

• Contribute to AI agents, prompt engineering, and automation layers within the product

• Continuously evolve systems based on real usage, scale, and constraints — not theoretical perfection

Security & DevSecOps Responsibilities

• Design and maintain secure AWS infrastructure across environments

• Enforce least-privilege IAM, network security, encryption, and secrets management

• Integrate security into CI/CD via IaC scanning, container security, and dependency checks

• Implement monitoring using CloudTrail, AWS Config, GuardDuty, Security Hub

• Drive incident response, vulnerability remediation, and compliance practices

What We’re Looking For

• 5+ years of hands-on experience building on AWS

• Strong understanding of distributed systems and scalable architecture

• Ability to convert ambiguous product ideas into clear technical systems and flows

• Proven experience building production-grade systems from scratch

• Comfortable operating with high ownership and evolving requirements

• Strong decision-making ability in unstructured environments

• Advanced proficiency in Infrastructure as Code (Terraform required)

• Experience designing and building data pipelines and data systems

• Hands-on with high-volume data processing and storage layersExperience deploying or supporting AI/ML systems in production

• Familiarity with RAG architectures, vector databases (OpenSearch, Pinecone, etc.)

• Strong understanding of containerized environments (EKS/ECS, Docker)

• Experience implementing monitoring using CloudWatch, Prometheus, Grafana

• Strong understanding of system performance, scaling, and reliability best practices

Good to Have

• Experience in early-stage startups or 0→1 environments

• Familiarity with event-driven architectures (Kafka, SQS, EventBridge)

• Strong understanding of cloud cost optimization and efficiency

What Success Looks Like

• Infrastructure built: Complete AWS setup from scratch

• System reliability: High uptime, low failure rates

• Deployment speed: Fast, reliable CI/CD pipelines

• Data pipelines: Scalable, accurate, low-latency systems

• AI systems: Successfully deployed and running in production

• Cost efficiency: Optimized cloud spend vs usage

• Security: Strong IAM, access control, and compliance posture

• Ownership: Ability to independently build, operate, and improve systems