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Dot Net Developer

Soma Shekar's profile picture
Posted by Soma Shekar
3 - 8 yrs
₹3L - ₹16L / yr
Bengaluru (Bangalore)
Skills
skill icon.NET
SQL
Agile/Scrum
Visual Basic (VB)

Good experience in programming Microsoft C# (preferred) and/or Visual Basic.NET, ADO.Net, and ASP.Net 2.0, .Net 4.5 framework or .net core 2.1 and above
Must have experience In SQL and Agile/Scrum

Nice to have experience in AWS or Azure

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Shubham Vishwakarma's profile image

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 Softtek

Founded :
1982
Type :
Products & Services
Size :
100-1000
Stage :
Profitable

About

Founded in 1982, Softtek is a global company helping organizations bridge the digital gap. With presence in North America, Latin America, Europe and Asia, Softtek provides Global 2000 organizations with technology solutions that create value through technology.
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Connect with the team

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Shilpa Pruthi
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Soma Shekar
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Shweta Raichur

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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's profile image

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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