Technical Manager

ROLES AND RESPONSIBILITIES:

• Plan, schedule, and manage all releases across product and customer projects.
• Define and maintain the release calendar, identifying dependencies and managing risks proactively.
• Partner with engineering, QA, DevOps, and product management to ensure release readiness.
• Create release documentation (notes, guides, videos) for both internal stakeholders and customers.
• Run a release review process with product leads before publishing.
• Publish releases and updates to the company website release section.
• Drive communication of release details to internal teams and customers in a clear, concise way.
• Manage post-release validation and rollback procedures when required.
• Continuously improve release management through automation, tooling, and process refinement.

IDEAL CANDIDATE:

• 3+ years of experience in Release Management, DevOps, or related roles.
• Strong knowledge of CI/CD pipelines, source control (Git), and build/deployment practices.
• Experience creating release documentation and customer-facing content (videos, notes, FAQs).
• Excellent communication and stakeholder management skills; able to translate technical changes into business impact.
• Familiarity with SaaS, iPaaS, or enterprise software environments is a strong plus.

PERKS, BENEFITS AND WORK CULTURE:

• Competitive salary package.
• Opportunity to learn from and work with senior leadership & founders.
• Build solutions for large enterprises that move from concept to real-world impact.
• Exceptional career growth pathways in a highly innovative and rapidly scaling environment.

Strong Lead DevOps / Infrastructure Engineer Profiles.

Mandatory (Experience 1) – Must have 7+ years of hands-on experience working as a DevOps / Infrastructure Engineer.

Mandatory (Experience 2) – Candidate’s current title must be Lead DevOps Engineer (or equivalent Lead role) in the current organization

Mandatory (Experience 3) – Must have minimum 2+ years of team management / technical leadership experience, including mentoring engineers, driving infrastructure decisions, or leading DevOps initiatives.

Mandatory (Experience 4) – Must have strong hands-on experience with Kubernetes (container orchestration) including deployment, scaling, and cluster management.

Mandatory (Experience 5) – Must have experience with Infrastructure as Code (IaC) tools such as Terraform, Ansible, Chef, or Puppet.

Mandatory (Experience 6) – Must have strong scripting and automation experience using Python, Go, Bash, or similar scripting languages.

Mandatory (Experience 7) – Must have working experience with distributed databases or data systems such as MongoDB, Redis, Cassandra, Elasticsearch, or Puppet.

Mandatory (Experience 8) – Must have strong hands-on experience in Observability & Monitoring, CI/CD architecture, and Networking concepts in production environments.

Mandatory (Company) – Candidates must be from Good / Well Funded / Early Stage Product-based companies.

Mandatory (Education) –B.E/ B.Tech

DevOps Systems Engineer with experience in Docker Containers, Docker Swarm, Docker Compose, Ansible, Jenkins and other tools. As part of this role she/he must work with the container best practices in design, development and implementation.

At Least 4 Years of experience in DevOps with knowledge of:

• Docker
• Docker Cloud / Containerization
• DevOps Best Practices
• Distributed Applications
• Deployment Architecture
• Atleast AWS Experience
• Exposure to Kubernetes / Serverless Architecture

Skills:

• 3-7+ years of experience in DevOps Engineering
• Strong experience with Docker Containers, Implementing Docker Containers, Container Clustering
• Experience with Docker Swarm, Docker Compose, Docker Engine
• Experience with Provisioning and managing VM's - Virtual Machines
• Experience / strong knowledge with Network Topologies, Network Research,
• Jenkins, BitBucket, Jira
• Ansible or other Automation Configuration Management System tools
• Scripting & Programming using languages such as BASH, Perl, Python, AWK, SED, PHP, Shell
• Linux Systems Administration -: Redhat

Additional Preference:

Security, SSL configuration, Best Practices

Key Responsibilities:-

• Collaborate with Data Scientists to test and scale new algorithms through pilots and later industrialize the solutions at scale to the comprehensive fashion network of the Group

• Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service to provide an e2e solution

• Leverage an understanding of software architecture and software design patterns to write scalable, maintainable, well-designed and future-proof code

• Design, develop and maintain the framework for the analytical pipeline

• Develop common components to address pain points in machine learning projects, like model lifecycle management, feature store and data quality evaluation

• Provide input and help implement framework and tools to improve data quality

• Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, designers, product managers and others to build the AI ecosystem within the Group

• Deliver on time, demonstrating a strong commitment to deliver on the team mission and agreed backlog