Design, build, and maintain core platform services, developer tools, automation, and infrastructure-as-code. Improve CI/CD, release automation, and cloud provisioning. Own features end-to-end and collaborate with engineering and product teams to enhance scalability, reliability, and developer productivity.
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI
C3 AI is looking for a highly motivated Senior Software Engineer - Platform to join our Platform Engineering team. You will play a critical role in designing, building, and maintaining the core platform features, frameworks, and development tools used to build enterprise-scale AI applications. Your work will directly support application development, platform scalability, and engineering productivity across the company.
Responsibilities:
- Design, build, and maintain core platform services, frameworks, and developer tools used across an enterprise-scale AI platform.
- Design and maintain robust automation for testing, integration, and deployment across a distributed development organization.
- Develop and maintain infrastructure automation to provision, manage, and improve cloud environments reliably and consistently.
- Build and maintain internal tools and services that improve engineering productivity, developer experience, and operational efficiency.
- Support engineering workflows, release automation, version control integration, code validation, and platform rule enforcement.
- Improve the reliability, scalability, maintainability, and operational quality of platform services, frameworks, and automation systems.
- Partner closely with software engineering and product management teams to gather requirements and deliver high-quality platform capabilities.
- Own features end-to-end, including design, documentation, implementation, testing, maintenance, and mentoring engineers on engineering standards and best practices.
Qualifications:
- B.S./M.S. in Computer Science, Engineering, or a related technical discipline.
- 3+ years of backend, platform, DevOps, infrastructure, or distributed systems engineering experience in production environments.
- Strong hands-on experience with Java and one or more scripting or automation languages such as Python, Shell, or Groovy.
- Experience designing, maintaining, and improving CI/CD pipelines, build systems, release automation, and testing workflows.
- Experience with infrastructure as code, preferably Terraform, and cloud environment provisioning or management.
- Familiarity with Go for infrastructure tooling, automation, or cloud platform development.
- Experience designing and developing scalable platform services, frameworks, APIs, developer-facing tools, or engineering workflow systems.
- Hands-on understanding of software development principles, design patterns, testing, debugging, observability, and performance analysis.
- Systematic problem-solving approach with a strong sense of ownership, independence, and operational accountability.
- Strong communication and interpersonal skills, with the ability to work across engineering, infrastructure, release, and product teams.
C3 AI provides excellent benefits, a competitive compensation package and generous equity plan.
California Base Pay Range
$145,000—$198,000 USD
C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
C3 AI Redwood, California, USA Office
Redwood, CA, United States
Similar Jobs
Financial Services
Designs and operates production-grade Python services, APIs, distributed systems, and cloud-native applications for enterprise machine learning platforms. The role uses AWS, infrastructure as code, observability tools, automated testing, CI/CD, and secure deployment practices. Responsibilities include architectural guidance, code reviews, mentoring, production support, resiliency engineering, and collaboration with product, platform, and site reliability teams. The engineer also helps adopt AI-assisted development practices and may build solutions using generative AI and large language models.
Top Skills:
Amazon EcsAmazon EksAmazon MskAmazon S3Amazon SqsApache KafkaAPIsAWSCi/CdCloudFormationDatadogDynatraceGenerative AiJavaLarge Language ModelsMicroservicesPythonSplunkTerraform
Financial Services
Leads development of secure, scalable cloud platforms optimized for AI and machine learning workloads. Designs and operates Kubernetes and containerized infrastructure, builds CI/CD and infrastructure-as-code automation, and optimizes cloud performance and costs. Partners with AI teams to translate compute needs into platform requirements, promotes observability and operational stability, and guides adoption of secure, responsible AI-assisted software development practices across engineering teams.
Top Skills:
C#Ci/CdCloud ComputingDockerGoGrafanaHigh Performance ComputingHybrid CloudIaasInfrastructure As CodeJavaKubernetesLinuxMachine LearningMicroservicesMl InferenceMl TrainingMlflowMlopsNoSQLNvidia BcmNvidia DcgmNvidia Dynamo InferencePaasPrivate CloudPrometheusPublic CloudPythonRay.IoSaaSSlurmSQLTransformer ArchitectureVllm
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Build and operate a security data platform connecting SIEM, identity, asset, threat intelligence, and knowledge graph systems. Design core APIs, distributed data pipelines, schemas, risk scoring, entity resolution, and coverage queries. Own architecture and platform workstreams from scoping through delivery, collaborate with detection and identity teams, review code, mentor engineers, and drive partner adoption. The role requires expert Python, deep Splunk expertise, cybersecurity experience, and senior-level project ownership.
Top Skills:
Asset InventoryAsynchronous Data PipelinesIdentity GovernanceKnowledge GraphsLarge Language ModelsMachine LearningMessage BusMitre Att&CkPythonRetrieval-Augmented GenerationSchema RegistrySIEMSplSplunkSplunk Apis
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
