Job Description

We are looking for engineers (backend heavy + AI Native) to join our tech team based in Kolkata. This role sits at the core of revenue infrastructure — covering payment orchestration, subscription lifecycle, and high-scale backend systems.

You won’t maintain systems. You’ll design, ship, and scale them. Every deployment impacts millions of users and real revenue.

What You’ll Own + Key Responsibilities :

Own end-to-end technical decisions — API contracts, data models, service boundaries, and integration patterns — across a live, high-traffic streaming platform.
Think architecturally first: identify the right abstraction, lead the trade-off conversation, and document decisions that the broader team can reason about and build on.
Use AI-native development tools (Cursor, Claude Code, GitHub Copilot) as your default workflow — not as shortcuts, but as force multipliers where you own the output and know when to override.
Lead technical design reviews for new capabilities, surfacing risks, edge cases, and cross-system dependencies before a single line gets committed.
Diagnose and resolve production issues across backend systems — trace root causes, write clean fixes, and prevent recurrence through deliberate design choices.
Partner closely with product, growth, content, and data teams to translate fast-moving business requirements into robust, maintainable backend solutions.
Contribute to hoichoi Cortex — our central data aggregation and intelligence layer — by designing clean API contracts and data flows that connect content signals, user behaviour, and business metrics.
Evaluate and integrate third-party services, LLM APIs, and external tools — making deliberate build-vs-buy-vs-compose decisions with clear justifications.
Review code that a future-you would be proud to maintain: readable, testable, and defensible.

If you have :

1–5+ years of backend engineering experience with production ownership — at least one system that real users depend on and you were responsible for.
Strong fundamentals in at least one backend language and comfort reasoning about system design, data modelling, and API contracts.
Ability to read a system, understand its constraints, and make architectural recommendations — not just execute tickets handed down to you.
Experience working in a fast-moving product team where requirements change mid-sprint and priorities shift without warning.
Default user of AI coding tools (Cursor, Copilot, Claude Code, etc.) on real shipped features — with at least one concrete example where AI generated significant code that you evaluated, debugged, or chose to override.
Comfort with ambiguity: you can move without complete information and know when to decide independently versus when to ask.

And (or) also have :

Familiarity with streaming or media tech: CDNs, adaptive bitrate, DRM, or video processing pipelines.
Experience with event-driven architectures, message queues (Kafka, SQS, RabbitMQ), or distributed microservices.
Prior work on data pipelines, analytics integrations, or internal developer tooling.
Exposure to LLM APIs, prompt engineering, or AI-augmented product features shipped to real users.

Candidates must have an active GitHub or portfolio for skill evaluation.