Engineering Manager

Armor Defense

. Lead and manage a high-performing AI-native software engineering team .

Posted 9/19/2026full-timePune • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading AI-native software engineering teams while delivering high-quality software solutions. Proficient in hands-on development, software architecture, and managing complex engineering processes across distributed teams.

Highest-signal resume keywords

AI-Assisted Development ToolsFrontend and Backend DevelopmentCloud Platform ExperienceSoftware Architecture SkillsTeam Leadership and Performance Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ReactTypeScriptC#Node.jsPythonGoDockerKubernetesSQLNoSQL

Soft Skills

Written CommunicationVerbal CommunicationMentorshipCoaching

Tools & Technologies

AWSAzureGitTerraformAnsibleVMware vSphereProxmoxNSX-TFortiMonitorRubrik

Industry Keywords

CybersecurityIncident ResponseData ProtectionPerformance TuningData Modeling

Tech Stack

Tools & technologies

AnsibleAWSAzureCloudCyber SecurityDockerJavaScriptKubernetesNode.jsNoSQLPythonReactSQLTerraformTypeScriptVMwareGo

About the role

Key responsibilities & impact

Lead and manage a high-performing AI-native software engineering team
Provide technical direction, mentorship, and hands-on guidance while building a culture of engineering ownership
Contribute directly to architecture, design, code reviews, and implementation of complex software
Own day-to-day delivery for assigned product areas, including feature work, defect triage, regression prevention, and customer escalations
Keep the Director, Engineering current on status and risk
Drive end-to-end engineering execution with minimal reliance on product management
Translate business objectives into working software
Execute release management discipline, including change windows, rollback criteria, and release readiness
Put AI-assisted development tools into daily engineering practice and measure effects on delivery speed and quality
Evaluate emerging AI frameworks, foundation models, developer tools, and cloud technologies
Hire and build the team, including defining the technical hiring bar, running interview loops, and onboarding engineers
Manage third-party technology vendor relationships, including platform usage, cost, performance, alternatives, renewals, negotiations, and build-versus-buy decisions
Collaborate with global and regional teams across distributed engineering teams
Manage team performance through one-on-ones, goal setting, performance reviews, coaching, and career development planning
Serve as escalation point for production incidents and customer-impacting issues
Coordinate rapid incident response, run post-incident reviews, and feed findings back into engineering practice

Requirements

What you’ll need

Demonstrated track record of shipping production software that customers depend on; the company does not screen on years on a resume
Experience leading or managing software engineers, including performance management, coaching, and career development
Hands-on production experience delivering software with AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, or equivalent
Strong frontend and backend development skills using technologies such as React, TypeScript, C#, Node.js, Python, or Go
Excellent software architecture skills
Production experience with AWS, Azure, or another major cloud platform
Ability to combine hands-on development with leadership responsibilities
Strong defect management and quality engineering instincts
Experience with Docker and Kubernetes
Working knowledge of Terraform or Ansible
Strong experience with relational, non-relational, and AI-enabled data platforms, including SQL and NoSQL databases, vector databases, data modeling, performance tuning, and scalable data architectures for AI applications
Experience in a customer-facing role providing technical advice and strategic direction
Git proficiency, including branching strategies, code review workflows, and CI/CD pipeline integration
Understanding of AI/LLM security risks, including prompt injection, data leakage, and model limitations
Ability to critically evaluate AI-generated output for accuracy and security implications
Strong written and verbal communication skills across distributed teams and time zones
Bachelor’s degree in Computer Science, Information Technology, or equivalent professional experience preferred
Experience with virtualization, infrastructure, and data protection technologies such as VMware vSphere, Proxmox, NSX-T, FortiMonitor, Zerto, and Rubrik preferred
Cybersecurity background covering XDR, MDR, SIEM, SOC tooling, endpoint detection and response, threat detection, incident response, and security monitoring preferred

Benefits

Comp & perks

Opportunity to shape the future of cybersecurity and help redefine the industry
Continuous learning and improvement encouraged
Career development planning
Full-time employment