Requirements
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
