Technical Lead

CUBE Bikes; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

CUBE is a global RegTech business leading in AI-powered regulatory intelligence for financial services. You will own the end-to-end Azure pipeline architecture across 8 stages, define API contracts, and mentor the squad to deliver scalable, reliable content processing.

In the first 90 days you will publish architecture blueprints, implement initial automation for stages 01 and 02, and establish a skeleton end-to-end pipeline in Azure with client-aligned QA integration.

Qualifications

• 5+ years in backend/distributed systems engineering with tech-lead or architect responsibilities.
• Expert in Python API development (FastAPI) and REST API design.
• Hands-on experience with Kafka or Azure Service Bus and event-driven architectures.
• Strong Azure cloud experience (compute, storage, networking, identity).
• Working knowledge of XML Schema and structured-content pipelines.
• Strong CS fundamentals: data structures and algorithms for high-volume pipelines.
• Proven system design capability — high-level and low-level designs, scalability and fault tolerance.
• Experience with performance engineering and APM tools like New Relic or Datadog.

Responsibilities

• Design the end-to-end pipeline architecture across 8 stages from intake to QA acknowledgement.
• Define API contracts for Stage 01, Stage 02, and Stage 08.
• Design event-driven patterns using Kafka/Azure Service Bus.
• Set coding, review, and deployment standards; lead technical design reviews.
• Mentor engineers across backend, monitoring, XML, and QA automation workstreams.
• Collaborate with Engineering Manager on sprint scoping, risk, and delivery sequencing.

Skills

Backend architecture

Python (FastAPI)

Event-driven design

Azure cloud

XML pipelines

CS fundamentals

System design

Performance tuning

Tools

FastAPI

Kafka

Azure Service Bus

XML Schema

New Relic / Datadog

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.

End-to-end architecture and API contracts for all three automation targets (intake, XML retrieval, QA acknowledgement) signed off by the RM platform and Publishing Team before Sprint 1 build begins. Stages 01, 02, and 08 operating via API with zero manual handoffs by pipeline launch. Design-related rework held below 10% of sprint capacity — measured through defect root-cause tagging. A design review process in place that the squad follows without escalation; no sprint blocked on an unresolved architectural decision. Success test: a new engineer can understand the pipeline from the architecture documentation alone within their first week.

About the Role

Own the end-to-end architecture of the content Azure pipeline — an 8-stage regulatory content pipeline spanning requirement intake, book monitoring, XML generation, file delivery, and QA acknowledgement. You will define API contracts and event-driven integration patterns, set engineering standards, and act as technical mentor to the squad.

Key Responsibilities

• Design the end-to-end pipeline architecture across all 8 stages, from requirement intake through XML delivery and QA acknowledgement.
• Define API contracts for the three automation targets: requirement intake (Stage 01), previous-version XML retrieval (Stage 02), and automated QA acknowledgement (Stage 08).
• Design event-driven integration patterns using Kafka / Azure Service Bus.
• Set coding, review, and deployment standards; lead technical design reviews.
• Mentor engineers across backend, monitoring, XML, and QA automation workstreams.
• Partner with the Engineering Manager on sprint scoping, technical risk, and delivery sequencing.

First 90 Days — Objectives

• Day 30 — Architecture blueprint and API contracts for all three automation targets published and signed off with RM platform and Publishing Team stakeholders.
• Day 60 — Stage 01 and Stage 02 automation designs implemented in the test environment; coding, review, and deployment standards adopted by the squad.
• Day 90 — Skeleton end-to‑end pipeline running in Azure across all 8 stages; Stage 08 QA‑acknowledgement integration design agreed with the client side.

Required Skills & Experience

• 5+ years of backend / distributed systems engineering, with prior tech-lead or architect responsibility.
• Expert in Python API development (FastAPI) and REST API design.
• Hands‑on experience with Kafka or Azure Service Bus and event‑driven architectures.
• Strong Azure cloud experience (compute, storage, networking, identity).
• Working knowledge of XML Schema and structured‑content pipelines.
• Strong computer science fundamentals: data structures and algorithms applied to high‑volume pipeline design.
• Proven system design and architecture design capability — HLD/LLD, scalability, fault tolerance, and capacity planning.
• Performance engineering: profiling, load analysis, and tuning of distributed services, with APM experience (New Relic, Datadog, or similar).

Nice to Have

• Experience in RegTech, publishing, or content‑processing platforms.
• Experience defining SLIs/SLOs with observability teams.
• Experience applying AI/LLM tooling in engineering workflows — AI‑assisted code review, Copilot‑style development, or LLM‑based document processing.

CUBE is an equal opportunity employer.

We celebrate diversity and are committed to creating an inclusive environment for all employees.