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Emergence AI is building next-generation agentic AI systems that move beyond code generation to provable task completion, verification, and long-horizon autonomy. Our Platform focuses on automating complex, mission-critical data workflows, from ingestion and transformation through analysis, decisioning, and action.

We work with customers in semiconductors, life sciences, and other data-intensive industries to turn fragmented, high-stakes data into trustworthy, continuously-operating AI Agents.

As a Staff AI Engineer at Emergence, You Will:

Bring AI expertise, product intuition, and a builder's mindset to advance the frontier of what agents can accomplish for our customers. You will work across applied research and engineering to solve many open problems in AI, including:

• Designing AI agent workflows and orchestration systems for our platform and solutions
• Designing optimal data representations and modes of interaction between agents and their environments
• Building verification and safety systems that enable autonomous agent execution in high-stakes enterprise environments

Representative Projects:

Workflow Orchestration & Custom Agent Builder. Build the platform that lets customers define their own investigation workflows from natural language to production-grade multi-step agents. Own the workflow execution engine, state management, error handling, versioning, and sharing capabilities that make custom workflows reliable and reusable.

Verification & Policy Engine. Design and implement the verification system that makes autonomous agent execution safe , policy-as-code frameworks, constraint checking, audit trails, and proof artifacts in an Enterprise systems. Enable agents to move to autonomous direction when verified safe.

Agent Operations & Observability. Build the provenance tracking, drill-down capabilities, and debugging tools that make agent behavior transparent and debuggable from query execution traces to multi-agent coordination visibility. Make non-deterministic AI systems observable and trustworthy.

Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Emergence measure and improve AI quality systematically , eval harnesses, ground truth management, regression detection, A/B testing for agents.

Context Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Emergence agent workflows depend on managing what agents see, remember, and pass between steps.

Responsibilities:

• Drive cutting-edge AI capabilities across multiple layers of the agent platform from workflow orchestration and verification systems to custom workflow builders and agent operations infrastructure.
• Ensure a high craft and quality bar in both AI agent performance and platform reliability , build systems that are fast, correct, and maintainable.
• Collaborate with fellow engineers, designers, product managers, and customers to integrate platform functionality into frontier agentic products and deliver customer value.
• Contribute to platform reliability, code quality, AI evaluation, testing, and maintenance across the broader engineering team.
• Mentor and elevate engineers around you , share knowledge, review code thoughtfully, and raise the technical bar for the team.

Required Qualifications:

• 8+ years of experience building backend systems, distributed systems, or data infrastructure, with at least 2+ years focused on AI/ML engineering in production environments.
• Experience building and shipping multi-model or multi-provider AI systems in production using LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, function calling, or agent frameworks at scale.
• Track record at both startups AND enterprise companies , you know how to move fast while maintaining reliability and can navigate both worlds effectively.
• Familiarity with context management, session state, or memory systems in AI or distributed systems. You've thought about what the model sees and why it matters.
• Experience with evaluation frameworks, testing strategies for AI systems, or quality measurement in production ML systems.
• Strong systems thinking around safety, verification, and correctness , you've built guardrails, validation layers, or compliance systems where "probably right" isn't good enough.
• Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.
• A bias toward full ownership: you navigate ambiguity well, don't wait for perfect specs, and take problems from concept through production deployment.
• Comfortable working with a small, fast-moving team where you'll dive in, take ownership, mentor others, and elevate the engineering culture.

Compensation Range: $200,000 to $230,000 USD

Emergence Benefits:

• Comprehensive health & wellness benefits, including medical, dental, vision, HSA, and FSA options
• Voluntary insurance offerings for additional coverage
• 401(k) plan with company match
• Flexible time off and company holidays to support rest and recharge
• Flexible remote work environment
• One-time home office setup stipend
• Ongoing monthly stipend to support your work-from-home needs