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Emergence AI

Orchestrates multi-agent AI for enterprise automation

AI Engineer - Prototyping

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeIrvine, CA, USA

About the Job

Requirements

  • At least 3 years of professional software engineering experience building production software.
  • Use Claude Code, Cursor, Codex, or similar AI development tools as part of a daily engineering workflow.
  • Have strong software engineering fundamentals and experience building production backend services, APIs, distributed systems, cloud applications, or developer platforms.
  • Be comfortable working across frontend, backend, infrastructure, or cloud services, and learn new languages and frameworks quickly.
  • Have experience building and shipping software used by real customers in production environments.
  • Have strong problem-solving skills, sound engineering judgment, and the ability to navigate ambiguity.
  • Have excellent communication skills and be able to collaborate effectively with customers, product managers, designers, and engineers.
  • Be self-driven, curious, and comfortable taking ownership in a fast-moving startup environment.

Responsibilities

  • Build customer-facing capabilities across the Enterprise Agent Platform, including agent orchestration, workflow execution, enterprise integrations, knowledge management, and administration.
  • Develop production-ready AI workflows and reusable platform services for enterprise solutions across multiple industries.
  • Design trusted AI capabilities, including evaluation, verification, observability, provenance, and human-in-the-loop workflows.
  • Build developer and user experiences that simplify how enterprise customers create, configure, and operate AI agents.
  • Work directly with enterprise customers to understand business problems, rapidly prototype solutions, and turn successful implementations into reusable platform capabilities.
  • Build the core platform that enables customers to create, configure, deploy, and operate AI agents securely at enterprise scale, including agent orchestration, workflow execution, context management, memory, governance, authentication, and enterprise integrations.
  • Partner with customers in semiconductor manufacturing, life sciences, and other industries to build production-ready AI workflows that automate complex business processes and transform customer-specific solutions into reusable platform capabilities.
  • Design and implement systems for trustworthy enterprise AI, including evaluation frameworks, verification pipelines, policy enforcement, audit trails, observability, provenance, and human-in-the-loop workflows.
  • Build capabilities that connect to enterprise data sources, discover schemas and semantic relationships, manage enterprise knowledge, and provide agents with context to reason over complex business data.
  • Develop the runtime for long-running AI workflows, managing execution state, retries, approvals, checkpoints, memory, and multi-agent coordination while ensuring reliability and transparency.
  • Design, build, and ship customer-facing capabilities across the Enterprise Agent Platform.
  • Own features from concept through production, balancing customer needs with long-term platform architecture.
  • Build high-quality software across the full stack using AI development tools to accelerate delivery while maintaining engineering quality.
  • Make engineering decisions about APIs, architecture, scalability, security, performance, and maintainability.
  • Work with Product Management, Customer Success, and enterprise customers to understand business problems and translate them into software.
  • Participate in customer workshops, technical discussions, solution design, and production deployments.
  • Iterate on customer feedback and evolve successful implementations into reusable platform capabilities.
  • Balance speed of delivery with building a platform that scales across customers and industries.
  • Design production-grade AI workflows with error handling, retry mechanisms, observability, auditability, and human-in-the-loop execution.
  • Build systems that are measurable, testable, debuggable, and reliable in production.
  • Improve platform quality through evaluation, monitoring, automation, and customer feedback.
  • Establish engineering best practices, reusable patterns, testing standards, and high-quality software engineering practices.
  • Evaluate emerging AI technologies and adopt those that improve engineering productivity and customer value.
  • Challenge assumptions, simplify complexity, and improve how software is designed and built.

Desired Qualifications

  • Experience building AI agents, agentic workflows, or enterprise AI applications.
  • Experience with large language models, tool calling, retrieval-augmented generation, context engineering, memory systems, or multi-agent orchestration.
  • Experience designing workflow engines, orchestration platforms, or distributed systems.
  • Experience integrating enterprise data sources such as databases, data warehouses, software-as-a-service applications, APIs, or document repositories.
  • Experience building developer tools, internal platforms, or engineering productivity systems.
  • Familiarity with Rust, Go, TypeScript, Python, or other modern programming languages.
  • Experience with cloud-native platforms, Kubernetes, observability, distributed tracing, or production operations.

About the Company

Emergence AI

Orchestrates multi-agent AI for enterprise automation

Emergence AI builds autonomous AI agents and orchestration systems that automate and scale enterprise workflows. Its flagship Emergence Orchestrator acts as a meta-agent that plans, assigns tasks to suitable models or agents, executes them, and verifies results via APIs or by navigating web interfaces. It can create new specialized agents in real time from natural language prompts, enabling recursive intelligence and broad interoperability with clients’ tools, data, and legacy systems. The goal is to enable collaboration among multiple AI agents to tackle complex tasks, improving efficiency and scalability for large organizations across industries like supply chain and semiconductor manufacturing, with a subscription-based API model.

Company size
51-200
Company stage
Late Stage VC
Total funding
$100M
Headquarters
New York City, United States
Founded
2018

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