Job Description

Sentra is the global leader in cloud-native data security for the AI era. The company’s mission is to empower organizations to confidently scale their data operations across multi-cloud and on-premises environments while leveraging the power of AI without compromising security.

Sentra’s unique approach enables enterprises to autonomously scan their environments without the need for agents, ensuring that data remains securely within their cloud or on-premises infrastructure. This innovative methodology sets us apart in the industry, providing organizations with control and visibility over their sensitive data at all times. Our commitment to excellence in data security posture management and data detection and response makes Sentra a leader in the field.

We're looking for a Backend & Deployment team lead to lead one of the most critical domains at Sentra — how our product is deployed, integrated, and operates within our customers' environments.

This is a highly hands-on leadership role, combining deep technical involvement with ownership of the domain and team. You will lead and grow a team of engineers while remaining closely involved in architecture, design, and critical parts of the system.

You will own the deployment domain end-to-end — from infrastructure and backend services to customer experience — and play a key role in shaping how Sentra delivers its product across AWS, Azure, GCP, and on-prem environments.

This role sits at the intersection of engineering, product, and customer-facing delivery, with direct impact on customer success and company growth.

Responsibilities

Team Leadership & Ownership

• Lead and grow the Backend & Deployment team, including hiring, mentoring, and developing engineers.
• Drive execution, prioritization, and delivery while maintaining high engineering standards.
• Foster a strong ownership culture and create clarity in a fast-paced, evolving environment.
• Take full end-to-end ownership of the deployment domain, including reliability, scalability, and customer experience.
• Partner closely with Product, R&D, Sales Engineering, and Customer Success to align priorities and deliver customer value.

Hands-on Technical Leadership

• Remain deeply involved in the system — contributing to architecture, design, and critical development efforts.
• Lead the design and evolution of deployment architectures across multi-cloud (AWS, Azure, GCP) and on-prem environments.
• Work hands-on with Kubernetes, Infrastructure-as-Code (Terraform), and backend services.
• Drive improvements in scalability, automation, observability, and resilience.

Collaboration & Customer-Facing Work

• Act as a technical escalation point for customer deployment and integration issues, working closely with Solutions Engineering and Support.
• Collaborate with external-facing teams (Customer Success, Solutions Engineering, Sales Engineering) on customer deployments and integrations, including participating in calls or troubleshooting sessions when needed — sometimes during US business hours.

Requirements

• Proven experience leading engineering teams.
• Strong experience with cloud platforms (AWS, Azure, or GCP).
• Solid experience with Infrastructure-as-Code (Terraform or similar) in production.
• Strong backend development experience (Python, TypeScript, or similar).
• Deep understanding of cloud networking, IAM, and distributed systems.
• Experience building and maintaining backend services — APIs, async workflows, or orchestration systems.
• Strong hands-on experience with Kubernetes.
• Ability to stay hands-on while leading a team.
• Experience working in customer-facing environments.
• Strong communication and leadership skills.
• High ownership mindset and ability to operate in ambiguous environments.

Nice to Have

• Experience leading teams in high-growth startups.
• Experience deploying infrastructure in customer-owned environments.
• Multi-cloud experience (AWS, Azure, GCP).
• Experience building deployment tooling, CLIs, or automation frameworks.
• Experience with monitoring, alerting, and distributed systems at scale.