Cognite - AI for Industry
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Senior AI Platform Engineer, Atlas AI
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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 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.
How you’ll demonstrate Ownership
We are seeking an AI Platform Engineer to join the Cognite Atlas AI Product team in Phoenix, AZ, to engineer, build, and operate the production-grade, multi-cloud platform that enables our internal and partner teams to build, deploy, and manage industrial AI agents. You will be responsible for creating the core services, frameworks, and infrastructure for our "agent builder workbench" and agent runtime, focusing on scalability, reliability, cost-efficiency, and security. Your work will directly impact industrial efficiency and sustainability, which is critical to our mission of powering a high-tech, sustainable, and profitable industrial future.
The Impact you bring to Cognite
- Design, build, and maintain the core Python SDKs and services for the Atlas AI platform. Create clean abstractions that empower Solution Engineers to easily define and test agents and workflows.
- Build the core agentic runtime, ensuring it is scalable, meets its SLOs, and can reliably manage the state, orchestration, and execution of industrial agents.
- Develop a robust, governed, and secure framework for AI agent tool-use. Engineer the platform components that allow solution engineers to safely add new tools (e.g., API calls, database queries) and that manage the secure execution, monitoring, and access control for those tools.
- Manage the LLM serving layer, including deploying and optimizing models for low-latency/high-throughput inference. Build and maintain model routing logic to select the most appropriate model (e.g., performance vs. cost) for a given task.
- Implement evaluation and observability for all AI services. Create standardized frameworks for systematically evaluating the performance, accuracy, cost, and safety of LLMs and agentic workflows. Drive the implementation of robust, automated testing strategies for LLM-based systems.
- Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, participating in on-call rotations, and ensuring a fast and effective incident response process.
- Work closely with the Lead Architect to translate the technical vision into implemented, production-grade services. Act as a key partner for the Solution Engineers (your internal customers) to understand their needs and abstract common patterns into reusable, robust platform components.
- Stay up to date on the latest developments in the field, and mentor junior developers.
Required Qualifications
- Bachelor's or Master’s degree in Computer Science or a related field, or equivalent practical experience.
- 8+ years of professional experience in backend software engineering, platform engineering, or MLOps, with a proven track record of architecting and operating complex systems at scale.
- 2+ years of hands-on experience building applications or platforms on top of AI/ML models or LLMs.
- Expert-level proficiency in Python and a strong background in software architecture, robust API design, and building maintainable, well-documented SDKs for other developers.
- Hands-on experience with Kubernetes (K8s) and building services on managed PaaS in a multi-cloud environment (AWS, Azure, GCP). Strong understanding of Infrastructure as Code (e.g., Terraform).
- Proven experience building and operating production-grade SaaS software. Understanding of the full development life cycle, including CI/CD, monitoring, telemetry, and on-call incident response.
- Practical experience with LLM orchestration frameworks (Bedrock, Vertex, Semantic Kernel, LangChain).
- Strong verbal and written communication skills, with the ability to articulate complex technical designs and decisions clearly.
Preferred Experience
- Hands-on experience deploying and managing LLMs in production using high-performance serving frameworks.
- Experience with MLOps/LLMOps tools for tracing, monitoring, and evaluating LLM applications (LangSmith, Arize, Phoenix, or equivalent).
- Experience with RAG Infrastructure, embedding generation pipelines, vector database integrations, and high-performance vector similarity search APIs.
A snapshot of our many perks and benefits as a Cogniter
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Senior Performance Engineer
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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 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.
We are seeking a Observability Engineer with strong expertise in designing, implementing, and optimizing observability solutions. In this role, you will be key to shaping the future of observability at Cognite, assessing existing observability frameworks, identifying gaps, and building robust capabilities encompassing log aggregation, event correlation, noise reduction, and comprehensive telemetry analysis to enable proactive operational excellence and reliability for our services.
The opportunity
Our core mission is to enhance the performance and reliability of our distributed microservices platform, which operates across AWS, Azure, and GCP and powers large-scale, user-facing applications.
We are expanding our Performance Engineering team and seeking motivated engineers. You will be expected to drive significant, measurable improvements in system performance and reliability, while also setting and upholding a higher performance standard across all our engineering teams.
Problem we are solving now:
- Driving Performance Ownership: Influence and guide engineering teams (squads) to integrate performance considerations into their daily workflows and prioritization, fostering a culture of performance ownership.
- Leading Performance Initiatives: Spearhead performance-focused projects that cover the entire Software Development Life Cycle (SDLC), from conception through deployment.
- Performance Bottleneck Resolution: Collaborate closely with various engineering teams and domains to pinpoint and eliminate performance bottlenecks across all services.
What you'll own
- Lead deep-dive performance investigations on critical services using metrics, logs, traces, and load testing
- Design and execute performance tests across, multi-cloud microservices environment
- Define performance baselines and non-functional requirem
What you bring
- 6 –10 years of performance engineering experience across large-scale distributed systems
- Strong hands-on experience with load testing tools — k6, Gatling, JMeter, or equivalent
- Deep proficiency with Grafana, Prometheus, and distributed tracing — query writing, alerting, and interpreting graphs
- Hands-on experience with Kubernetes, including resource management and scaling behaviour
- Practical experience across at least two of AWS, Azure, or GCP — and how cloud-specific behaviour affects system performance
- Ability to diagnose complex performance issues end-to-end — latency, throughput, resource saturation, inter-service dependencies
- Experience designing and executing performance tests in live or production-constrained environments
- Solid experience with CI/CD pipelines and Git-based workflows — including integrating performance tests into build and deployment stages
- Strong automation mindset — scripting, tooling, and building frameworks that scale beyond manual execution
- Ability to convert technical findings into clear, actionable recommendations for both engineering and product audiences
- Proven ability to influence engineering teams and drive performance improvements without direct authority
- Prior experience establishing or evolving a performance engineering practice within an engineering organisation
Good to have
- Profiling experience across JVM, Go, or Python
- Exposure to chaos engineering principles and tooling
- Experience defining non-functional requirements from scratch with product and architecture teams
- Exposure to AI-assisted engineering tools — Cursor, Claude, Copilot, or similar — and an appetite for applying them to automate performance workflows
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Observability Engineer (SRE/AI)
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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 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.
We are seeking a Observability Engineer with strong expertise in designing, implementing, and optimizing observability solutions. In this role, you will be key to shaping the future of observability at Cognite, assessing existing observability frameworks, identifying gaps, and building robust capabilities encompassing log aggregation, event correlation, noise reduction, and comprehensive telemetry analysis to enable proactive operational excellence and reliability for our services.
How you’ll demonstrate Ownership
- Conduct assessments of existing observability architectures to identify gaps and improvement opportunities.
- Design and implement scalable log aggregation pipelines for centralized and efficient data collection.
- Apply noise-reduction techniques to filter irrelevant or false-positive alerts, enhancing focus on actionable issues.
- Develop and maintain monitoring dashboards that deliver actionable insights across applications and infrastructure.
- Lead the migration from Lightstep to Honeycomb, ensuring seamless data pipeline transitions, OpenTelemetry alignment, and stakeholder adoption.
- Collaborate with infrastructure and product teams to integrate observability tooling into CI/CD workflows and cloud environments.
- Analyze telemetry data (metrics, logs, traces) to troubleshoot complex system behaviors and recommend improvements.
- Participate in production debugging and incident troubleshooting using telemetry data
- Mentor junior engineers on log management, event correlation, distributed tracing, and alert management.
- Stay current on observability innovations and recommend adoption strategies aligned with organizational goals.
- Support post-incident reviews and continuous improvement through data-driven root cause analysis.
- Drive continuous improvement in reliability and operational excellence through proactive observability initiatives.
The Impact you bring to Cognite
- 3+ years of experience in software or systems engineering, with at least 3 years focused on observability or SRE practices.
- Hands-on experience with observability tools such as Honeycomb, VictoriaMetrics, Lightstep, Prometheus, Grafana, OpenTelemetry, Splunk, Datadog, or New Relic.
- Strong knowledge of OpenTelemetry instrumentation (metrics, traces, logs) and SLIs/SLOs for reliability tracking.
- Experience with distributed tracing, event correlation, and noise reduction frameworks.
- Proficiency in one or more programming/scripting languages such as Python, Java, Kotlin, Go, or Shell.
- Working knowledge of Infrastructure as Code (Terraform) and CI/CD (Jenkins, Github Actions,...) pipelines.
- Familiarity with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
- Strong analytical, troubleshooting, and communication skills with the ability to work effectively across teams.
- Experience conducting observability gap assessments and defining improvement plans.
- Experience working in complex or multi-cloud environments is preferred.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Frontend DevEx Engineer
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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 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.
How you’ll demonstrate Ownership
As a Frontend DevEx Engineer, you’ll play an important role in building and improving the developer experience for our Product engineers. You’ll collaborate with top-tier domain and industry experts: designers, product managers, backend developers, ML engineers, 3D developers, and business leaders. We support one another, ask incisive questions, and give constructive feedback. Our goal is to leverage our diverse strengths and backgrounds to build innovative products, think outside the ordinary, and nurture a truly great culture. We’re seeking a proactive and skilled engineer who is passionate about quality and user satisfaction.
The Impact you bring to Cognite
- Contribute to architectural discussions and the implementation of scalable solutions across a diverse technology landscape, taking ownership of your tasks from concept to deployment.
- Develop and maintain solutions for developers that genuinely help them get their jobs done.
- Build and implement elegant APIs, intuitive user experiences, and the underlying infrastructure.
- Actively contribute to shaping the developer experience in Cognite.
- Work closely with our skilled developers to understand their needs and build products that help them succeed.
Required Qualifications
- You write well-structured, efficient, and maintainable code and actively champion code quality.
- You possess solid knowledge of modern JavaScript and TypeScript, with proven hands-on experience in frontend frameworks (e.g., React, Angular, Vue, or similar component-based architectures).
- Familiarity with CI/CD, build tooling (Webpack, Vite), and testing frameworks is highly valued.
Preferred Experience
- You love making users happy and are committed to creating products they truly want to use.
- You are capable of prioritizing your tasks and working efficiently to optimize your impact on the team’s goals.
- You’re comfortable learning new coding languages and adopting the best tools for the job.
A snapshot of our many perks and benefits as a Cogniter
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Senior Software Engineer - (Full Stack)
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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 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
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not step back - you’ll feel at home here. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future.
Focus: React Architecture / Backend development
The Mission
Cognite is looking for a Senior Software Engineer (Full Stack) who is a master of the React ecosystem. You are the "Engineer's Engineer"—the person teams turn to for complex UI challenges. You embrace a "Bootstrap" mindset: lean, automated, and relentlessly focused on reusability and high-velocity delivery.
Tactical Impact
- React Mastery: Lead the development of our most intricate React components and data-visualization tools using TypeScript and modern styling (Tailwind/Bootstrap).
- Developer Experience (DX): Build and maintain the tooling, CI/CD, and testing strategies (Vitest/Playwright) that allow our React teams to move fast.
- Optimization: Deep-dive into re-render bottlenecks and bundle sizes to ensure a "snappy" industrial-grade user experience.
- Backend Developer (Bonus): Ability to navigate a Kotlin/Java codebase to understand APIs or refine data models is a "nice to have" that will help you move faster.
Leadership & Influence
- Technical Mentorship: Lead by example through code reviews and pair programming, setting the bar for React best practices.
- Cross-Functional Collaboration: Work closely with Product and Design to translate complex industrial requirements into technical reality.
The Profile
- Expert-Level Frontend: 5+ years of experience in professional fullstack development with deep expertise in the modern Java, Golang, C++, JavaScript ecosystem, including React and TypeScript.
- Expertise: Mastery of React.js, State Management (Zustand/Redux), and CSS-at-scale.
- Full-Stack Familiarity (Bonus): Any experience with JVM languages (Kotlin/Java) is a plus
- The Bootstrap Spirit: A passion for building modular, themeable, and automated systems.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Database Engineer Reliability
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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 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.
How you’ll demonstrate Ownership
We need a DBRE who views "Cloud" as just another API. You will spend your time writing Go code to bridge the gaps between different cloud providers, ensuring our stateful services (Postgres, Kafka, Elasticsearch) behave consistently regardless of the underlying infrastructure.
What you will do:
- Multi-Cloud Automation: Develop Go-based tools and Kubernetes Operators to manage the lifecycle of 1,000+ clusters across AWS, GCP, and Azure.
- Cloud-Agnostic Resilience: Design and test failover strategies that account for cloud-specific nuances (e.g., storage latency variances). Design database architecture based on RTO, RPO, HA, and disaster recovery.
- Unified Observability: Build a "single pane of glass" for database health (SLIs/SLOs) that aggregates telemetry from diverse cloud environments and on-prem deployments.
- Hybrid-Cloud Strategy: Evaluate when to use a Cloud Provider’s native DBaaS vs. when to run our own self-managed clusters on Kubernetes to avoid vendor lock-in.
- Advanced Engineering: Solve high-complexity challenges including Customer Managed Encryption Keys (CMEK), automatic database resizing/splitting, and mitigating "noisy neighbor" problems.
The Impact you bring to Cognite
- Software Engineering: Professional-grade Go (Golang) experience. You prefer building controllers and automation over manual cloud-console clicking.
- Ideal candidate will be 3 - 5 years of experience.
- Database Internals: Deep knowledge of Postgres, Kafka, or Elasticsearch. You understand replication lag, WAL shipping, and partition rebalancing in distributed environments.
- Kubernetes Mastery: Experience with StatefulSets, CSI drivers, and the Operator pattern. You know how to make Kubernetes behave when the "state" is high-stakes.
- Multi-Cloud Fluency: Experience managing stateful workloads across at least two major clouds (GCP/Azure/AWS).
- Operational Grit: Experience in a 24/7 high-availability environment. You understand that "Reliability" is a feature that must be engineered, not just monitored.
Location: Bangalore, India (Hybrid)
Team: Database Reliability Engineering (DBRE)
Tech Stack: Go (Golang), Kubernetes, PostgreSQL, Kafka, Elasticsearch.
Cloud Environments: Multi-cloud (AWS, Azure, GCP and On-Prem/Private Cloud).
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Senior Database Engineer Reliability
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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 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.
How you’ll demonstrate Ownership
We need a DBRE who views "Cloud" as just another API. You will spend your time writing Go code to bridge the gaps between different cloud providers, ensuring our stateful services (Postgres, Kafka, Elasticsearch) behave consistently regardless of the underlying infrastructure.
What you will do:
- Multi-Cloud Automation: Develop Go-based tools and Kubernetes Operators to manage the lifecycle of 1,000+ clusters across AWS, GCP, and Azure.
- Cloud-Agnostic Resilience: Design and test failover strategies that account for cloud-specific nuances (e.g., storage latency variances). Design database architecture based on RTO, RPO, HA, and disaster recovery.
- Unified Observability: Build a "single pane of glass" for database health (SLIs/SLOs) that aggregates telemetry from diverse cloud environments and on-prem deployments.
- Hybrid-Cloud Strategy: Evaluate when to use a Cloud Provider’s native DBaaS vs. when to run our own self-managed clusters on Kubernetes to avoid vendor lock-in.
- Advanced Engineering: Solve high-complexity challenges including Customer Managed Encryption Keys (CMEK), automatic database resizing/splitting, and mitigating "noisy neighbor" problems.
The Impact you bring to Cognite
- Software Engineering: Professional-grade Go (Golang) experience. You prefer building controllers and automation over manual cloud-console clicking.
- Ideal candidate will be 6-10 years of experience.
- Database Internals: Deep knowledge of Postgres, Kafka, or Elasticsearch. You understand replication lag, WAL shipping, and partition rebalancing in distributed environments.
- Kubernetes Mastery: Experience with StatefulSets, CSI drivers, and the Operator pattern. You know how to make Kubernetes behave when the "state" is high-stakes.
- Multi-Cloud Fluency: Experience managing stateful workloads across at least two major clouds (GCP/Azure/AWS).
- Operational Grit: Experience in a 24/7 high-availability environment. You understand that "Reliability" is a feature that must be engineered, not just monitored.
Location: Bangalore, India (Hybrid)
Team: Database Reliability Engineering (DBRE)
Tech Stack: Go (Golang), Kubernetes, PostgreSQL, Kafka, Elasticsearch.
Cloud Environments: Multi-cloud (AWS, Azure, GCP and On-Prem/Private Cloud).
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Senior Machine Learning Engineer
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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 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 Opportunity
We are building the next generation of contextual AI for Industrial Operations. Our team focuses on transforming unstructured, complex industrial data—ranging from technical manuals to complex piping and instrumentation diagrams (P&IDs)—into structured, actionable intelligence. We leverage state-of-the-art Deep Learning, Generative AI, and Computer Vision to drive efficiency, safety, and operational excellence.
About the Role
As a Senior Machine Learning Engineer, you will be the engine of our contextualization initiatives, taking independent ownership of complex ML features from conception to production. You will bridge the gap between data science and software engineering, building the models and the surrounding infrastructure that parse complex industrial documents, extract multimodal entities, and interpret intricate engineering diagrams.
To be clear: this is an engineering-first role. We are not just looking for researchers to build isolated models; we need builders who write production-grade code, build robust APIs, and solve complex infrastructure problems. You will treat ML models as software components integrated into a highly scalable archite
How you’ll demonstrate Ownership- System-minded, focused on maintainability, rigorous testing, and automated pipelines for reliable ML production.
- Thrives in ambiguity, independently defining the technical path, selecting tools judiciously, and driving solutions to completion.
- Elevates team code quality through constructive reviews and informal mentorship, bridging the gap between research and production
The Impact you bring to Cognite
Key Responsibilities
- Take product requirements and independently design, train, test, and deploy ML models (e.g., NLP, Vision-Language Models) for document parsing, layout analysis, and entity matching.
- Write high-quality, scalable production code (Python). Wrap your ML models into robust RESTful or gRPC APIs and integrate them seamlessly into existing industrial master data systems and workflows.
- Implement and maintain CI/CD pipelines for your models. Navigate complex deployment environments, manage containerized applications (Docker/Kubernetes), and optimize inference bottlenecks.
- Work with Principal engineers to translate high-level system architectures into concrete, scalable data pipelines and production-ready microservices.
- Design automated testing for ML pipelines. Monitor deployed models in production for data drift, latency, and accuracy, proactively implementing retraining strategies.
- Collaborate effectively with product managers to define ML capabilities. Provide code reviews and informal technical mentorship to engineers.
Required Skills and Qualifications
- Bachelor’s or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
- 6–10 years of industry experience in software engineering with a strong focus on machine learning, MLOps, and API development.
- Strong programming skills in Python with experience using backend web frameworks (e.g., FastAPI, Flask, Django) to serve models.
- Solid expertise in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
- Hands-on experience with containerization (Docker, Kubernetes), Linux environments, CI/CD tools (GitHub Actions, Jenkins), and deploying models on cloud platforms (AWS, Azure, or GCP).
- Solid understanding of software architecture, data structures, and algorithms to ensure performant code.
- Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Ray, Dask) and orchestrating complex data workflows (e.g., Apache Airflow, Dagster, Prefect).
What Sets your Role Apart
- Independently define the technical ML/SWE approach for ambiguous feature requests and deliver to production.
- Recognize the model is a small part of the solution; expertly manage aspects like API rate limiting, asynchronous processing, and robust data routing around ML components.
- Possess hands-on experience maintaining production ML models and designing resilient systems against poor data quality..
Preferred Qualifications
- Proven experience fine-tuning and deploying multimodal models for visual data and engineering diagrams in live environments.
- Built robust, production-grade RAG pipelines, expertly utilizing Vector/Graph Databases for high-accuracy entity retrieval.
- Familiar with orchestrating multi-step reasoning using frameworks like LangGraph or AutoGen for real-world problem-solving.
- Strong understanding of advanced OCR, layout parsing, and techniques for consistent structured JSON extraction from complex industrial PDFs. Manufacturing/OT dataset experience preferred.
- Ability to optimize LLMs/VLMs for inference latency (quantization, TensorRT, vLLM), potentially in constrained, on-premises environments.
- Experience with modern data lake/lakehouse architectures (Delta Lake, Iceberg, Databricks) for efficient querying and preprocessing of petabyte-scale unstructured data for LLM/VLM training and RAG.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Senior Software Engineer
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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 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.
How you’ll demonstrate Ownership
- Build high-performance data pipelines using Spark, Flink, and Kafka to process terabyte-scale industrial datasets.
- Develop low-latency APIs and services supporting thousands of concurrent users with sub-second response times.
- Optimize time-series, sensor, and operational data storage and retrieval for massive scale.
- Engineer distributed processing solutions, including real-time streaming that handles millions of events per second.
- Design and evolve cost-efficient data lake architectures (S3/GCS) using modern formats like Parquet/ORC.
- Optimize OLAP query performance across systems such as ClickHouse, Pinot, or Druid.
- Build fault-tolerant, highly-available systems with circuit breakers, retries, and distributed tracing.
- Drive technical innovation through research, prototyping, and contributions to open-source.
- Collaborate with product and architecture teams to translate complex industrial data problems into scalable, production-grade solutions.
The Impact you bring to Cognite
- Deep expertise in Spark internals, including Catalyst optimizer, partitioning, and performance tuning.
- Strong hands-on experience with Flink/Kafka for both streaming and batch workloads.
- Proven ability to scale systems to 10K+ QPS with strong foundations in JVM performance, GC tuning, and memory management.
- Experience building high-throughput REST/gRPC services and advanced caching with Redis/in-memory data structures.
- Strong understanding of monitoring and observability (Prometheus, Grafana, OpenTelemetry).
- Solid architectural thinking with an ability to design distributed, secure, and resilient platforms.
- Collaborative mindset with the ability to work across engineering, product, and platform teams.
- 6–12 years of experience in distributed data systems, backend engineering, or platform engineering.
- Strong programming skills in Scala, Java, or Python.
- Experience with cloud platforms (AWS/GCP/Azure) and data lake/object storage.
- Prior experience with large-scale data, OLAP systems, or industrial/IoT data is a plus.
- Contributions to open-source or experience in industrial data/AI platforms is an added advantage.
What we offer:
- Opportunity to build world-class Industrial DataOps systems powering global energy, manufacturing, and industrial AI customers.
- A fast-growing, high-ownership environment in Cognite’s India R&D Center.
- Work on cutting-edge distributed systems, streaming architectures, AI-ready data platforms, and industrial-scale challenges.
- A culture that rewards innovation, autonomy, continuous learning, and open-source contribution.
- Competitive compensation, equity, and benefits aligned with Cognite’s global standards.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
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