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Salary
$25k – $62k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 4+ years exp
Overview
Company
Impact
Profile match
Aivar Innovations is a tech company delivering IT services with a focus on AI, ML, and cloud solutions to help businesses drive digital transformation by developing AI-powered platforms and voice AI solutions.

Responsibilities:

  • Own accelerator's 6-n stage processing pipeline end-to-end: Ingestion to output.
  • Build the connectors, PII/PHI safety layer, compliance audit trail, and multi-tenant isolation.
  • Pure platform engineering, async Python, event-driven architecture, and enterprise-scale reliability.
  • Design the core pipeline orchestration framework with async Python, supporting parallel/sequential stage execution with retry and dead-letter queues.
  • Build the connector framework for 50+ enterprise data sources (APIs, databases, file systems, SaaS platforms).
  • Implement safety validation, PII/PHI detection, data integrity checks, format compliance, and input sanitization.
  • Build the reconstruction module transforming extracted data into Markdown/vector representations and context maps.
  • Design event-driven architecture with message queuing, backpressure handling, and graceful degradation.
  • Implement immutable audit trail logging across all 6 stages for every decision, action, and transformation.
  • Build multi-tenant data isolation, ensuring strict customer separation at every pipeline stage.

Requirements:

  • Experience: 4-8 years | 2+ years building data-intensive pipelines.

Must-Have Technical Skills:

  • Distributed Python systems: asyncio, aiohttp, and Celery; not scripting.
  • Message queues/streaming Kafka, SQS, RabbitMQ, or Redis Streams.
  • High-volume data pipelines: 100K+ documents/records per batch.
  • API design: REST/GraphQL, versioning, rate limiting, and auth.
  • AWS services: Lambda, SQS/SNS, MSK, EKS, Step Functions, ECS/EKS, S3 DynamoDB, and RDS.
  • Multi-tenant SaaS architecture and customer data isolation patterns.
  • Production habits: comprehensive testing, CI/CD, monitoring, and incident response.
  • Core Tech Stack: Python, FastAPI, Celery, asyncio, Kafka/SQS/Redis Streams, PostgreSQL, DynamoDB, Redis, Elasticsearch, Terraform/CDK, Prometheus/Grafana/OpenTelemetry, GitHub Actions, Docker, and AWS (Lambda, ECS, Step Functions, S3).
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