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Java Developer
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Java Developer

Ramsha Ansari's profile picture
Posted by Ramsha Ansari
4 - 9 yrs
₹10L - ₹20L / yr
Remote only
Skills
skill iconJava
J2EE
skill iconSpring Boot
Hibernate (Java)
API
RESTful APIs
JSON
skill iconXML
Oracle
Microservices
Agile/Scrum

Java Developer Job Description

We are looking for a Java developer responsible for building Java applications.

Responsibilities

  • Design, build and maintain efficient, reusable, and reliable Java code
  • Identify bottlenecks and bugs, and devise solutions to these problems
  • Help maintain code quality, organization, and automatization.

Skill Set:

  • Proficient in Java, with a good knowledge of its ecosystems
  • Java, Rest API integration, JSON, XML, Oracle, Microservices, Agile Scrum.
  • Experience in developing large-scale distributed systems.
  • API knowledge
  • Solid understanding of object-oriented programming
  • Familiar with various design and architectural patterns
  • Skill for writing reusable Java libraries
  • Spring, Spring Boot, Spring Cloud, React native
  • Experience: 04 to 10 years
  • Salary: As Per Market
Work from Home
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About the Schnell Apps

Founded :
2018
Type :
Services
Size :
20-100
Stage :
Profitable

About

SCHNELL APPS is Software Development Company.
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Ramsha Ansari

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Role overview

The client is building a multimodal AI platform that processes multi-hour video, audio and text to generate structured insights, narratives and highlight workflows for broadcasters and media organisations.

 

We are seeking a Backend / Platform Engineer to design and build high-throughput media pipelines, robust APIs, and model-serving infrastructure that connect our AI engine (video perception + multimodal reasoning) to real products and customer environments.

 

This is not a CRUD‑only backend role.

 

You will work on:

  • long‑running jobs
  • distributed processing
  • GPU inference orchestration
  • storage for embeddings and metadata
  • integration with AI models
  • reliability and observability at scale

 

Key responsibilities

Media ingestion & processing pipelines

  • Design and implement ingestion pipelines for multi‑hour video and audio content.
  • Build microservices for frame extraction, audio processing, transcription integration and metadata generation.
  • Handle long‑running, asynchronous jobs using queues, workers and robust retry strategies.
  • Integrate with FFmpeg or similar tools for transcoding, segmenting and preparing media for AI models.

API & platform architecture

  • Design and implement REST/gRPC APIs that expose AI model outputs (perception, multimodal alignment, narratives) to frontend and external systems.
  • Define clear contracts for internal services and external integrations.
  • Implement authentication, authorisation and rate‑limiting for platform endpoints.
  • Ensure backward‑compatible API evolution as the product matures.

Model‑serving & AI integration

  • Integrate with AI inference services (video models, multimodal models, LLM/VLM) running on GPUs or specialised infrastructure.
  • Design request/response flows that handle large payloads, streaming outputs and structured results.
  • Optimise throughput and latency for inference pipelines, including batching, caching and concurrency control.
  • Collaborate closely with AI engineers to productionise models and debug end‑to‑end behaviour.

Storage, data models & performance

  • Design data models to store embeddings, timelines, metadata, scene/shot boundaries, and narrative units.
  • Work with appropriate storage technologies (SQL/NoSQL, object storage, search indices) based on access patterns.
  • Implement indexing and query strategies for fast retrieval of segments, highlights and multimodal insights.
  • Optimise performance for large datasets and high‑volume workloads.

Reliability, observability & operations

  • Implement logging, metrics and tracing across services for debugging and monitoring.
  • Set up health checks, circuit breakers and graceful degradation for critical services.
  • Work with CI/CD pipelines to ensure safe, repeatable deployments.
  • Collaborate on Kubernetes‑based deployments (or equivalent orchestration) for scaling services.

 

Requirements (must‑have)

Experience:

  • 4–8 years in backend or platform engineering.
  • At least 3 years working on distributed systems, high‑throughput services or complex pipelines (not just simple CRUD apps).

Languages & frameworks:

  • Strong proficiency in Python or Node.js (one primary, both are a plus).
  • Experience with at least one modern backend framework (FastAPI, Flask, Express, NestJS, etc.).

Distributed systems & pipelines:

  • Hands‑on experience with queues and workers (e.g. Celery, RabbitMQ, Kafka, SQS, etc.).
  • Experience building asynchronous, long‑running job pipelines.
  • Understanding of idempotency, retries, backoff, and failure handling.

APIs & integration:

  • Strong experience designing and implementing REST APIs (gRPC is a plus).
  • Experience integrating with external services and handling network‑level failures.

Cloud & infrastructure:

  • Experience deploying services on AWS, GCP or Azure (EC2/Compute Engine, S3/GCS, IAM, networking basics).
  • Experience with Docker; exposure to Kubernetes is a strong plus.

Data & storage:

  • Experience with SQL and at least one NoSQL store.
  • Ability to design schemas and data models for performance and maintainability.

Engineering quality:

  • Strong debugging skills across services and environments.
  • Experience with unit/integration tests for backend systems.
  • Clear, structured communication in English.

 

Nice‑to‑have

  • Experience with media/video processing (FFmpeg, transcoding, segmenting).
  • Experience with AI/ML model integration (serving models, handling inference requests).
  • Experience with search/retrieval systems (e.g. Elasticsearch, vector databases).
  • Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
  • Experience working with remote teams across time zones.

 

What we are explicitly NOT looking for

To reduce noise and mismatches, we are not looking for:

  • Pure CRUD‑only backend developers with no pipeline or distributed systems experience.
  • Engineers who have only worked on small, single‑service apps without scale or complexity.
  • Candidates who cannot explain trade‑offs in architecture, data modelling and reliability.
  • Candidates who are uncomfortable with ownership of subsystems end‑to‑end.

 

Why join us

  • Work on real, complex problems at the intersection of media, AI and distributed systems.
  • Collaborate with senior AI engineers working on perception, multimodal fusion and narrative reasoning.
  • Build the core platform that turns AI models into a usable product for broadcasters and media organisations.
  • Operate with high ownership, clear expectations and direct access to the CTO.
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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