Website:
valeriegroup.com
Job details:
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
Click on Apply to know more.