About Emergence AI

Emergence AI is a frontier agentic AI lab advancing safe, autonomous AI through its pioneering neuroformal architecture. We are building the next generation of enterprise AI: systems capable of understanding complex knowledge, reasoning across information, executing multi-step workflows, and taking action with the verifiability and reliability required for mission-critical environments.

Our Enterprise Agent Platform provides the foundation for building, deploying, and operating AI systems in production — from data connectivity and knowledge management to workflow orchestration, observability, evaluation, and governance. We partner with organizations in semiconductor manufacturing, life sciences, and other data-intensive industries to solve complex challenges that require trusted AI systems capable of operating in real-world environments.

Our team brings experience from leading AI research labs and technology companies, including IBM Research, The Allen Institute for AI, Amazon, and Broadcom. With headquarters in New York and offices across California, Spain, and India, we bring together diverse expertise and perspectives to tackle some of the most challenging problems in enterprise AI.

About the Role

As an AI Engineer, you'll build customer-facing capabilities across Emergence's Enterprise Agent Platform, working directly with Product Management, Customer Success, and enterprise customers to turn complex business problems into production-grade AI systems. You'll operate as an AI-native engineer, using AI development tools to accelerate delivery while owning architecture, engineering quality, and customer outcomes. We care more about engineering judgment, ownership, and the ability to learn than expertise in any specific language or framework.

You'll

Build the core Enterprise Agent Platform that lets customers create, configure, deploy, and operate AI agents securely at scale, including agent orchestration, workflow execution, context management, memory, governance, and enterprise integrations.
Partner with customers in semiconductor manufacturing, life sciences, and other data-intensive industries to build production-ready AI workflows, then turn those customer-specific solutions into reusable platform capabilities that benefit every customer.
Design the systems that make enterprise AI trustworthy, including evaluation frameworks, verification pipelines, policy enforcement, audit trails, observability, provenance, and human-in-the-loop workflows.
Build the data and knowledge capabilities that connect to enterprise data sources, discover schemas and semantic relationships, and give AI agents the context needed to reason accurately over complex business data.
Develop the runtime that powers long-running AI workflows, managing execution state, retries, approvals, checkpoints, memory, and multi-agent coordination while ensuring reliability and transparency.
Work directly with Product Management, Customer Success, and enterprise customers in workshops, technical discussions, and production deployments to rapidly understand problems and ship solutions.
Own features from concept through production, making thoughtful engineering decisions around APIs, architecture, scalability, security, and performance.
Raise the engineering bar by establishing reusable patterns and best practices, evaluating emerging AI tools for what meaningfully improves engineering productivity, and continuously simplifying how we build.

You'll Have

3+ years of professional software engineering experience building production software.
AI-native engineer who uses Claude Code, Cursor, Codex, or similar AI development tools as part of your daily engineering workflow, not just a tool you occasionally reach for.
Strong software engineering fundamentals — production backend services, APIs, distributed systems, cloud applications, or developer platforms — and comfortable working across the stack, picking up new languages and frameworks quickly.
Experience building and shipping software used by real customers in production environments.