Devops Engineer & Architect

Get My SaaSTech Lead - DevOps Engineer & Architect

Position Type: Full-Time

Location: Remote

Reports To: Founder & Tech Advisors

1. Role Summary

This role is pivotal in architecting, planning, and executing the backend infrastructure of an AI-powered SaaS marketplace. The scope includes both SaaS operations and AI/ML pipelines. The candidate must possess hands-on expertise in Infrastructure as Code (IaC), cloud-native architectures, DevOps automation, and cross-functional team leadership. Ownership, innovation, and delivery excellence in a dynamic startup environment are non-negotiable.

2. Engagement Scope

2.1 Type of Engagement

• Full-time role with flexible hours.
• Remote-first and async collaboration culture.
• Performance will be evaluated through weekly deliverables and progress checkpoints.
• Requires structured autonomy and tight coordination with engineering and AI/ML teams.

2.2 Work Nature

• Deliverable-based execution (not hourly tracking).
• Requires proactive ownership, clear communication, and occasional contributions outside core responsibilities due to startup constraints.

3. Key Responsibilities3.1 Initial Phase: Planning & Architecture (2 Weeks)

• Gather technical requirements across AI/ML, data, and backend teams.
• Finalize cloud architecture (AWS-centric) with cost-efficient, open-source tooling where applicable.
• Design infrastructure encompassing:
• SaaS backend services
• ML training/inference pipelines
• Monitoring and observability stack
• CI/CD systems
• Security/compliance (IAM, VPC, WAF)
• Develop a roadmap using Terraform or other IaC tools (Pulumi, CDK).
• Evaluate modern ISE platforms (e.g., System Initiative, Cortex, Morpheus Data) for integration potential.

3.2 Development Phase (Weeks 4-8)

• Provision AWS resources using Terraform and integrate GitOps pipelines.
• Set up AI/ML infrastructure with AWS SageMaker, Bedrock, and open-source alternatives.
• Implement DevOps automation:
• CI/CD pipelines (CodePipeline, GitOps)
• Serverless APIs with Lambda/API Gateway
• Containerized deployments (Fargate, ECS, EKS)
• Deploy observability tools:
• Logging (OpenTelemetry)
• Monitoring (Prometheus, Grafana)
• Alerting and incident management
• Ensure production-grade reliability with autoscaling, failover, and DR mechanisms.

3.3 Cross-Functional Leadership (Ongoing)

• Lead infrastructure planning and execution with:
• AI/ML Engineers (for model training/inference)
• Data Engineers (ETL, pipelines)
• Full-stack Developers (backend APIs, DB infrastructure)
• Drive hiring/resource planning for backend and DevOps functions.
• Own infrastructure-level decisions and performance/cost optimizations.

3.4 Continuous Responsibilities (Weekly)

• Lead weekly sprints and 1:1 check-ins.
• Maintain technical documentation (architecture, configs, deployment workflows).
• Monitor system health and proactively resolve issues.
• Improve DevOps maturity via internal tooling, workflow automation, and incident response practices.
• Stay current with trends in MLOps, AIOps, and serverless Ops; recommend new tools or upgrades.

4. Required Technical Competencies

• Cloud Infrastructure: Expert-level AWS (EC2, Lambda, EKS, SageMaker, IAM, VPC).
• IaC & GitOps: Deep experience with Terraform, Pulumi, AWS CDK, GitOps-based automation.
• AI/ML Infrastructure: Familiarity with ML pipelines, GPU workloads, AutoML, inference serving, model versioning.
• DevOps/MLOps: Strong in Docker, Kubernetes, CI/CD best practices, AIOps tooling.
• Observability: Experience deploying logging, metrics, alerting systems; focus on reliability.
• Tool Evaluation: Ability to assess and implement cost-effective, open-source, enterprise-grade solutions.

5. Required Soft Skills & Attributes

• Proven leadership in managing technical teams.
• Ability to convert business goals into execution-ready tech plans.
• Strong communication and collaboration skills.
• High ownership and bias toward action.
• Precision in planning, execution, and documentation.
• Startup mindset: adaptable, proactive, outcome-driven.

6. Collaboration & Reporting

• Interfaces with:
• AI/ML Engineers
• Data Engineers
• Backend Developers
• Project Manager (Founder)
• Tools:
• Communication, Documentation & PM: Using a project & work scope tracker and communicator
• Cadence:
• Weekly sprint planning & retrospectives
• Asynchronous daily updates

7. Deliverables & KPIs

• Deliverables and KPIs will be finalized post the initial 2-week planning phase.
• Development roadmap must incorporate inputs from technical advisors and will be used to track performance.
• Milestones will align with sprint-based execution and weekly progress reviews.

8. Special Notes

• Supported by a core team including:
• AI/ML Engineer
• Backend and frontend developers
• Data Engineer
• While the company is bootstrapped, support is available - but initiative and adaptability are essential.
• This role is foundational to establishing scalable, secure, and reliable infrastructure.