Support Analyst

Cube; Bengaluru; On-site; INR 900,000 - 1,400,000; Full time

Job summary

CUBE is hiring for a Production Support / Backend Engineer to join our RegTech backend team in Bengaluru. You will provide L3 production support, own incident response, and develop Python-based utilities to automate operational tasks and improve system reliability.

You will work on enterprise applications, AI/data pipelines, and backend services, building REST APIs, automating deployments, and monitoring health with observability tools. 1-2 years in related roles is ideal.

Qualifications

• 1–2 years of experience in Production Support or Backend Ops.
• Strong Python backend development skills.
• Experience with FastAPI or Django.
• Proficient in Linux, Bash and SQL.
• Familiar with Docker, CI/CD and cloud platforms.

Responsibilities

• Provide L3 support for production applications and data pipelines.
• Investigate, troubleshoot, and resolve incidents and performance issues.
• Develop Python utilities to automate repetitive tasks.
• Build REST APIs and backend enhancements for operational workflows.
• Automate deployments and recovery procedures with Python/Bash scripts.
• Monitor health using observability tools and perform root cause analysis.
• Collaborate with Engineering to reduce technical debt and improve reliability.
• Maintain runbooks and incident reports for continuous service improvements.

Skills

Python programming

REST APIs

Linux

Bash

Debugging

SDLC understanding

Distributed systems

Tools

Docker

Git

CI/CD

AWS

FastAPI

Datadog

Prometheus

Job description

CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.

Why us?

CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally.

In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead.

We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.

With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.

We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting‑edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.

Key Deliverables — What Success Looks Like

Ensure high availability and operational stability of production systems.

Reduce incident resolution time through automation and engineering improvements.

Deliver Python-based tools and backend enhancements that eliminate repetitive operational work.

Contribute production bug fixes, performance improvements, and operational features to the core product.

Improve application reliability, monitoring, and developer productivity through continuous enhancements.

About the Role:

Provide L3 production support while contributing to the development and continuous improvement of enterprise applications, AI/data pipelines, and backend services. Own incident response, operational stability, automation and bug fixes while developing Python-based solutions to improve system reliability, reduce manual effort, and enhance engineering productivity.

Key Responsibilities:

• Provide L3 support for production applications, backend services, APIs, and data processing pipelines.
• Investigate, troubleshoot, and resolve production incidents, application failures, and performance issues.
• Develop and maintain Python applications, automation tools, and utilities to improve operational efficiency.
• Build REST APIs, backend enhancements, and automation scripts for operational workflows.
• Develop Python/Bash scripts to automate recurring operational tasks, deployments, and recovery procedures.
• Monitor application health using observability and APM platforms; perform root cause analysis and implement permanent fixes.
• Work with Engineering teams to resolve defects, improve application reliability, and reduce technical debt.
• Maintain runbooks, operational documentation, and incident reports while driving continuous service improvements.

First 90 Days — Objectives

Day 30: Understand the application architecture, support processes, and production environment.

Resolve production incidents independently and deliver initial automation scripts.

Day 60: Develop Python-based utilities and backend enhancements to automate operational tasks.

Contribute bug fixes, monitoring improvements, and operational tooling.

Day 90: Own end-to-end production support for assigned services while actively contributing to product development.

Reduce recurring incidents through automation, code improvements, and root cause elimination.

Required Skills & Experience:

• 1-2 years of experience in Production Support, Platform Engineering, Backend Development, or Technical Operations.
• Strong programming skills in Python with experience building backend applications, REST APIs, and automation tools.
• Experience with FastAPI, Django, or similar Python frameworks.
• Good understanding of REST APIs, microservices, and distributed systems.
• Strong Linux, Bash, and shell scripting skills.
• Experience with PostgreSQL, SQL, and troubleshooting data-related issues.
• Hands‑on experience with Docker, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
• Experience with monitoring and observability tools such as Grafana, Prometheus, New Relic, Datadog, or OpenTelemetry.
• Strong debugging, log analysis, performance tuning, and root cause analysis skills.
• Good understanding of software development lifecycle and engineering best practices.

Nice to Have:

Experience with Kafka, RabbitMQ, or event‑driven architectures.

Experience supporting AI/ML or data processing pipelines.

Exposure to Generative AI or LLMs for operational automation, incident summarization, or intelligent runbook generation.

Knowledge of Kubernetes and Infrastructure as Code.

Familiarity with ITIL processes, SRE practices, and enterprise SaaS applications.

Interested?

If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.