Role Overview:
As a Tech Lead DevOps, youll own the end-to-end cloud architecture, lead large-scale production setups, and drive platform reliability for our fraud detection and trust systems. Youll operate at a strategic level while staying hands-onguiding teams, influencing engineering decisions, and working directly with clients to design robust, scalable infrastructure.
If you enjoy solving complex infra challenges, leading from the front, and building production systems that scalethis role is for you.
We are the perfect match if:
- Have 9-12+ years of experience in DevOps / Cloud / Platform Engineering
- Have deep expertise in cloud platforms (AWS / GCP / Azure) with the ability to design architecture from scratch
- Have successfully implemented multiple production-grade cloud setups end-to-end
- Are highly proficient with Infrastructure as Code (Terraform / CloudFormation, etc.)
- Have strong experience with CI/CD systems (GitLab CI / Jenkins / GitHub Actions) and DevSecOps practices
- Have hands-on expertise in Kubernetes, containerization, and microservices-based architectures
- Understand observability, monitoring, and reliability engineering (Prometheus, Grafana, ELK, etc.)
- Can lead, mentor, and drive technical decision-making across teams
- Have strong communication skills and can confidently operate in client-facing environments
- Bring an automation-first mindset with a focus on scalability, reliability, and performance (Bonus)
- Have exposure to ML Ops / data platforms
Heres what your day will look like:
- Design and own end-to-end cloud architecture for IDfys platform ensuring scalability, security, and cost efficiency
- Lead and implement production-grade infrastructure setups across cloud environments
- Define and drive DevOps strategy, standards, and best practices across teams
- Architect and optimize CI/CD pipelines, release processes, and deployment strategies
- Build and evolve highly available, fault-tolerant, and resilient systems
- Drive Infrastructure as Code adoption and standardization across projects
- Own observability, monitoring, alerting, and incident response frameworks
- Collaborate with engineering, product, and data teams to enable DevOps / ML Ops ecosystems
- Act as a technical leader in client discussions, translating requirements into scalable solutions
- Mentor engineers, review designs, and guide teams on best practices and architecture decisions
- Proactively identify risks, optimize costs, and drive continuous improvement across infrastructure
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