---
title: 'Principal Software Engineer (workflow / platform) at Cognite - AI for Industry'
canonical: 'https://feeny.ai/job/principal-software-engineer-workflow-platform-cognite-ai-for-industry-bengaluru-1yzdazdf1g9c'
type: 'job'
last_seen: '2026-09-09'
---

# Principal Software Engineer (workflow / platform) at Cognite - AI for Industry

- **Company:** Cognite - AI for Industry
- **Location:** Bengaluru, India
- **Posted:** 2026-09-07
- **Last confirmed live:** 2026-09-09
- **Apply:** https://job-boards.eu.greenhouse.io/cognite/jobs/4912128101

## Job description

What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.

Our [Moonshot](https://www.cognite.com/en/company/newsroom/cognite-s-industrial-ai-momentum-soars-driving-ecosystem-impact-at-global-conference) is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.

Our [Moonshot](https://www.cognite.com/en/company/newsroom/cognite-s-industrial-ai-momentum-soars-driving-ecosystem-impact-at-global-conference) is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

## About The Role

We're seeking a Principal Software Engineer who excels at building high-performance distributed systems and thrives in a fast-paced startup environment. You'll be working on cutting-edge data infrastructure challenges that directly impact how Fortune 500 industrial companies manage their most critical operational data.

## How you’ll demonstrate Ownership

- Platform Ownership: Design, build, and operate the core serverless execution engine and Workflows orchestration layer that serve as foundational primitives for CDF’s AI and automation capabilities.
- Reliability Engineering: Own uptime, latency SLOs, and incident response for platform services ensuring Functions execute deterministically and Workflows progress without data loss or silent failures.
- Scalability: Architect for multi-tenant & multi-cloud, high-throughput workloads. Design scheduling, queueing, and retry mechanisms that degrade gracefully under pressure.
- API Design: Define and evolve clean API-first architecture, versioned REST and event-driven APIs that downstream engineering teams and external customers depend on.
- Observability: Instrument services with distributed tracing, structured logging, and alerting (Open-telemetry / Prometheus / Grafana / Honeycomb stack) so failures surface before customers notice.
- CI/CD & Testing: Champion test automation - unit, integration, and smoke tests and maintain deployment pipelines that ship to production with confidence.
- Performance: Profile and resolve bottlenecks in execution throughput, cold-start latencies, and cross-service call chains driving a “snappy” platform experience for industrial workloads.
- Cost Efficiency (Bonus): Model compute and storage costs for functions execution; identify and implement optimizations that reduce cloud spend without sacrificing reliability.

The Impact you bring to Cognite

- 10+ years of Engineering: Proven track record building and operating production backend services at scale.
- Expertise: Deep mastery of JVM languages (Kotlin preferred, Java acceptable), Python(FastAPI), distributed systems patterns, and cloud-native service design (Kubernetes, Azure, GCP, AWS, Private cloud).
- Workflow & Orchestration: Hands-on experience with workflow engines (Conductor, Apache Airflow, or equivalent) and event-driven architectures (Kafka, Pub/Sub).
- Data & Storage: Comfortable working with relational databases (PostgreSQL) & non-relational databases, object storage(Data-lakes), and caching layers (Redis) in multi-tenant environments.
- Observability Stack: Practical experience with Open-telemetry, Prometheus, and Grafana for instrumentation and operational insight.
- ML Platform Exposure: experience supporting ML workloads & notebooks in production, whether through job scheduling, resource management, experiment tracking integration, or model serving infrastructure.
- Contextualisation Domain (Bonus): Familiarity with industrial knowledge graph construction, entity resolution, or NLP/CV pipelines as they relate to industrial asset data is a strong differentiator.
- Full-Stack Awareness (Bonus): Familiarity with React or TypeScript is a plus for consuming and dogfooding your own platform’s developer tooling.
- The Platform Thinking Spirit: A passion for building composable, well-documented, and automated platform systems that empower other engineers including ML engineers to build faster.

Good to have

ML Platform & Contextualisation:

- ML Workload Support: Build and extend platform primitives compute scheduling, environment management, and secrets handling, that enable ML engineers to run model training, fine-tuning, and batch inference jobs reliably.
- Contextualisation Pipelines: Support the engineering infrastructure behind Cognite’s Contextualisation capabilities (entity matching, asset hierarchy inference, P&ID parsing) by ensuring the platform can orchestrate long-running, GPU-aware, and data-intensive ML workflows without manual intervention.
- Vector & Embedding Infrastructure (Bonus): Familiarity with serving or storing vector embeddings to support semantic search and RAG-based contextualisation use cases.
- Model Lifecycle Awareness: Understand model versioning, A/B experiment tracking, and the boundary between platform concerns and ML framework concerns, so the platform stays lean while ML teams stay unblocked.

Learn more about us

- [Impact 2025](https://www.cognite.com/en/resources/blog/key-highlights-from-impact-2025)
- [Cognite's Industrial AI: Moonshot](https://www.cognite.com/en/company/newsroom/cognite-s-industrial-ai-momentum-soars-driving-ecosystem-impact-at-global-conference)
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

## Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

## About Cognite - AI for Industry

## Company Overview
- **One-liner**: Cognite delivers industrial AI software that unifies siloed operational data to help energy, process manufacturing, and other industrial companies improve production efficiency and scale AI solutions.
- **Entity Type**: Private (backed by Aker ASA, total funding of $338.9M)
- **Headquarters**: Tempe, Arizona, United States (global HQ; also Lysaker, Norway)
- **Founded**: 2016
- **Founders**: Not publicly available (co-founded by a team with industrial and tech backgrounds)

## Core Business
- **Primary industries**: Industrial AI, Industrial DataOps, Energy (oil & gas, renewables), Process Manufacturing, Power & Utilities
- **Target customers**: B2B – enterprise industrial companies (energy, manufacturing, chemicals, etc.)
- **Mission or purpose**: “Power a high-tech, sustainable, and profitable industrial future” — enabling industrial teams to move faster, work safer, and achieve more with AI.

## Products & Services
- **Cognite Data Fusion®**: Open Industrial DataOps platform that contextualizes operational, engineering, and IT data into a real-time Industrial Knowledge Graph, making data accessible for AI and analytics. (SaaS/platform)
- **Cognite Atlas AI™**: Low-code industrial AI agent workbench for building and deploying agentic AI to automate complex operational tasks. (AI agent platform)
- **Cognite Flows™**: Tool for building and scaling production-ready industrial workflows 100x faster. (Workflow automation)
- **Composable reference applications**: Pre-built solutions for production optimization, smart maintenance, workforce digitalization, and sustainability.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding $338.9M (5 rounds); Annual revenue SEK 790.7M (approx. $75M based on current exchange rates, but exact USD not given)
- **Notable Investors/Partners**: Parent company Aker ASA; partners include Microsoft, Aker BP, Sopra Steria, Omny, Aize, and others. Recognized as a Leader in IDC MarketScape for Industrial DataOps Platforms.
- **Growth Signals**: 663 employees (+20.9% YoY); 102 active job postings (+67.2% YoY); LinkedIn followers 103,713 (+65.8% yearly); committed to delivering $100B in customer value by 2035; customers report 30-80% reduction in maintenance time and 4-month deployment cycles.

## Competitive Advantages
- **Industrial domain expertise**: Deep specialization in heavy industry (energy, process manufacturing) with a platform built for complex OT/IT data integration.
- **Open ecosystem**: Works with any cloud, any data source, any LLM, enabling flexible partnerships and off-the-shelf integrations.
- **Low-code AI agents**: Cognite Atlas AI allows domain experts to build AI agents without deep coding, speeding adoption.
- **Proven ROI**: Customers report 10x productivity improvements, rapid scaling (e.g., from pilot to 9 facilities in months), and significant downtime reduction.

## Strategic Focus
- **Scaling industrial AI**: Accelerate time-to-value with pre-built solutions, AI agents, and use-case best practices.
- **Global expansion**: Growing presence in Americas (Tempe, Austin, Houston), Europe (Oslo), Asia (Tokyo, Bengaluru).
- **Customer value commitment**: Ambitious goal of $100B in customer value by 2035.
- **Partner ecosystem**: Deepening integrations with cloud providers, system integrators, and industrial software vendors.

## Why Work Here
- **Culture**: Values of Relentless (innovation, learning from setbacks), Ownership (shared responsibility, inclusivity), and Impact (result-oriented, adding value to team and customers). Described as “smart, passionate builders, and problem solvers.”
- **Remote/Hybrid/Office**: Hybrid model with offices in Tempe, Austin, Houston, Oslo, Tokyo, Bengaluru. Some roles listed as “USA (remote)” indicating flexibility for certain positions.
- **Diversity**: Employees from 60+ countries; global team of engineers, product managers, domain experts.
- **Perks & Growth**: Opportunity to work on “biggest impact on our planet” — industrial AI at scale; strong investment in R&D and career development; fast-growing company with 100+ open roles.
- **Engineering culture**: Emphasis on AI, data engineering, machine learning, and full-stack development; roles like Senior AI Engineer, ML Engineer, Data Engineer, Applied AI Engineer.

## Sources
1. [cognite.com](https://www.cognite.com/en)
2. [cognite.com](https://www.cognite.com/en/company/about-us-cognite)
3. [cognite.com](https://www.cognite.com/en/company/careers)
4. [linkedin.com](https://www.linkedin.com/company/cognitedata)
5. [cbinsights.com](https://www.cbinsights.com/company/cognite)

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