Rearc Logo

Rearc

AI Native Software Engineer

Reposted 7 Days Ago
Remote
Hiring Remotely in United States
Junior
Remote
Hiring Remotely in United States
Junior
The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.
The summary above was generated by AI


Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments.


This role focuses on building production systems, agent-based workflows, integrating AI platforms, and delivering scalable, cloud-native solutions. You’ll work across the full lifecycle — from system design through to production deployment — building AI-powered applications that integrate into real business workflows. This is a 100% hands-on engineering role, requiring strong software engineering fundamentals alongside practical experience with modern AI systems.


What You Bring
  • 8–10+ years of software engineering experience
  • Strong experience building cloud-native systems, including APIs, microservices, containers, and serverless architectures
  • Proven experience building and deploying AI/LLM-based systems in production (e.g. RAG, agents, orchestration workflows)
  • Hands-on experience with AI platforms (e.g. OpenAI, Anthropic, Google Vertex, or similar)
  • Experience designing and implementing:
    • Retrieval systems (RAG)
    • Agent workflows and orchestration
    • Tool/function invocation patterns
  • Strong understanding of system-level trade-offs (performance, cost, latency, reliability)
  • Experience with CI/CD pipelines, infrastructure as code, and production observability
  • Proficiency in Python, Java, or similar backend languages
  • Experience debugging and optimising production systems


Preferred Experience
  • Experience with agent frameworks (e.g. LangGraph, AutoGen, CrewAI)
  • Experience designing multi-agent or distributed AI systems
  • Familiarity with enterprise-scale system integration
  • Experience optimising AI workloads for cost and performance
What You'll Do
  • Design and implement AI agents, including RAG pipelines, orchestration workflows, and tool invocation
  • Build evaluation frameworks to measure system accuracy, latency, and reliability
  • Implement observability and monitoring across the AI system lifecycle
  • Integrate with AI providers and build abstraction layers to support multi-model and multi-provider architectures
  • Optimise AI systems for performance, cost, and scalability
  • Develop cloud-native services using microservices, containers, and serverless patterns
  • Build and deploy AI-powered applications aligned to business workflows
  • Integrate AI systems into existing enterprise platforms and APIs
  • Define and execute testing strategies for AI systems
  • Measure and improve system performance (latency, throughput, accuracy, cost)
  • Debug and optimise production systems
  • Collaborate with client and internal engineering teams
  • Participate in technical design discussions, focused on implementation


About Rearc

At Rearc, we're committed to empowering engineers to build awesome products and experiences. Success as a business hinges on our people's ability to think freely, challenge the status quo, and speak up about alternative problem-solving approaches. If you're an engineer driven by the desire to solve problems and make a difference, you're in the right place!


Our approach is simple — empower engineers with the best tools possible to make an impact within their industry.


We're on the lookout for engineers who thrive on ownership and freedom, possessing not just technical prowess, but also exceptional leadership skills. Our ideal candidates are hands-on-keyboard leaders who don't just talk the talk but also walk the walk, designing and building solutions that push the boundaries of cloud computing.


Founded in 2016, we pride ourselves on fostering an environment where creativity flourishes, bureaucracy is non-existent, and individuals are encouraged to challenge the status quo. We're not just a company; we're a community of problem-solvers dedicated to improving the lives of fellow software engineers.


Our commitment is simple - finding the right fit for our team and cultivating a desire to make things better. If you're a cloud professional intrigued by our problem space and eager to make a difference, you've come to the right place. Join us, and let's solve problems together!


Your first few weeks at Rearc will be spent in an immersive learning environment where our team will help you get up to speed. Within the first few months, you’ll have the opportunity to experiment with a lot of different tools as you find your place on the team.


Rearc is committed to a diverse and inclusive workplace. Rearc is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Similar Jobs

12 Days Ago
Remote or Hybrid
Santa Clara, CA, USA
201K-352K Annually
Senior level
201K-352K Annually
Senior level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Design, build, and operate production-grade agentic AI systems: multi-agent orchestration, enterprise-grounded reasoning using CMDB/Knowledge Graph, retrieval/RAG pipelines, model integration with frontier SDKs, and trust/safety/governance. Lead architecture, code quality, and mentor engineers for scalable, safe autonomous agents.
Top Skills: AnthropicC++CmdbGoGoogle (Ai Sdks)Hybrid SearchInference OptimizationJavaKnowledge GraphLlm Fine-TuningMlopsModel ObservabilityOpenaiPrompt EngineeringPythonRagRe-RankingRetrieval Evaluation MetricsVector StoresWorkflow Data Fabric
Yesterday
Remote
USA
119K-217K Annually
Senior level
119K-217K Annually
Senior level
Kids + Family • Mobile
Lead Android-first development of growth experiments and features, using AI-native workflows to design, implement, instrument, and analyze A/B tests. Ship performant, reliable Android experiences at scale, mentor teammates, participate in on-call, and codify AI-native engineering playbooks for broader adoption.
Top Skills: A/B TestingAgentic WorkflowsAmplitudeAndroid StudioAndroid View SystemBitriseClaude CodeClean ArchitectureCrashlyticsCursorDaggerDatabricksEppoExposure LoggingFastlaneFeature FlaggingFlowGithub ActionsGithub CopilotGradleGrowthbookHiltJetpack ComposeJetpack ViewmodelKotlinKotlin CoroutinesLaunchdarklyLlmsMacrobenchmarkMavenMviMvvmNavigationOptimizelyPerfettoPrompt EngineeringSegmentSnowflakeStatsigSystrace
5 Days Ago
Remote
USA
119K-217K Annually
Senior level
119K-217K Annually
Senior level
Kids + Family • Mobile
Build and operate high-throughput experimentation and recommendation infrastructure. Design APIs and services, use agentic AI workflows (LLMs) for development, ensure performance and reliability, participate in on-call, mentor teammates, and codify AI-native engineering practices.
Top Skills: Apache KafkaAWSClaude CodeConfluent CloudConfluent PlatformContainerized DeploymentsCursorDatadogFeature StoresFlinkGithub ActionsGithub CopilotGrafanaJavaKafka StreamsLlmsMavenNexusPrometheusSchema RegistrySpring Boot

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

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account