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Senior Software Engineer - Platforms

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Senior Software Engineer - Platforms in Others new

  • Cognite - AI for Industry
  • Full time
  • Email
  • Bengaluru, India

Responsibilities

  • Design, build, and operate the serverless execution engine and Workflows orchestration layer.
  • Own uptime, latency SLOs, incident response, deterministic execution, and failure handling for platform services.
  • Architect scalable multi-tenant and multi-cloud scheduling, queueing, retry, and execution systems.
  • Define and evolve versioned REST and event-driven APIs.
  • Implement distributed tracing, structured logging, alerting, and operational observability.
  • Maintain automated unit, integration, and smoke testing and production deployment pipelines.
  • Profile and optimize execution throughput, cold-start latency, cross-service calls, and cloud costs.
  • Build platform primitives that support ML scheduling, environment management, secrets handling, training, fine-tuning, and batch inference workflows.
  • Support infrastructure for industrial contextualisation pipelines, including entity matching, asset hierarchy inference, and P&ID parsing.
  • Contribute to vector and embedding infrastructure, model lifecycle support, and developer tooling where applicable.

Requirements

  • 6–8 years of experience building and operating production backend services at scale.
  • Deep expertise in JVM languages, with Kotlin preferred and Java acceptable.
  • Strong Python and FastAPI experience.
  • Experience with distributed systems patterns and cloud-native service design.
  • Hands-on experience with Kubernetes, Azure, GCP, AWS, or private cloud environments.
  • Experience with workflow engines such as Conductor or Apache Airflow and event-driven architectures using Kafka or Pub/Sub.
  • Experience with relational and non-relational databases, object storage, data lakes, and caching layers such as Redis.
  • Practical experience with OpenTelemetry, Prometheus, and Grafana.
  • Experience supporting production ML workloads, notebooks, job scheduling, resource management, experiment tracking, or model-serving infrastructure.
  • Familiarity with industrial knowledge graphs, entity resolution, NLP or computer-vision pipelines, or contextualisation is advantageous.
  • Familiarity with React or TypeScript is a plus.
  • Understanding of model versioning, A/B experiment tracking, vector embeddings, and RAG-based contextualisation is beneficial.

Cognite - AI for Industry

Cognite is the only Industrial Data and AI platform built for scaling. We help Energy, Manufacturing, and Power & Utilities companies break down data silos and turn complex operational data into actionable, enterprise-wide value. Why Cognite? Unify: Cognite Data Fusion® unifies OT, ET, and IT dat...

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