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Emergence AI

Orchestrates multi-agent AI for enterprise automation

VP Engineering

Engineering LeadershipPosted on Nov 12
Full-timeNew York, NY, USA$250k - $350k

About the Job

Requirements

  • Build with agents hands-on and have a clear point of view on how review, testing, and quality should change when agents write code.
  • Have led engineering for a product customers depend on and been accountable for shipping it.
  • Have changed a team from long plans and large releases to continuous, incremental delivery, achieving a significant increase in speed while maintaining or improving quality.
  • Turn strategy into measurable outcomes and an execution plan a team can deliver.
  • Demonstrate strong technical judgment in design reviews, production readiness, and assessing which decisions are difficult to reverse.
  • Have several years of direct engineering management experience, including hiring, candid feedback, addressing underperformance, and developing people into larger roles.
  • Have built useful engineering career paths and developed a view on how growth and leveling should change when agents write code.
  • Communicate clearly and concisely, and know when a demo is more effective than a document.
  • Move quickly, act independently, work effectively amid ambiguity, and learn as tools change.
  • Have led teams across countries and time zones using effective written communication and hand-offs.
  • Most candidates will have 15 or more years of engineering experience, including several years leading teams; demonstrated accomplishments and ability to learn are most important.

Responsibilities

  • Ship working software to customers continuously in small, verified increments, measuring customer impact rather than plans or activity.
  • Manage and grow a team of engineers by setting expectations, providing candid feedback, recognizing strong work, maintaining performance standards, and addressing performance issues promptly.
  • Provide engineers with growth opportunities through stretch work, meaningful ownership, pairing, and regular career conversations grounded in shipped work; define growth in an agent-assisted engineering environment.
  • Hire exceptional AI-native engineers and develop their effectiveness with agents and product thinking; share effective practices and emphasize outcomes.
  • Translate engineering principles into daily practices, evolve them as tools change, and retire practices that no longer add value.
  • Translate leadership charter and product direction into clear customer outcomes and success criteria that people and agents can execute and check automatically.
  • Identify and remove workflow delays such as hand-offs, approvals, meetings, and slow checks, replacing processes with automation where risk permits.
  • Lead through working software, prototyping before specification, iterating features rapidly before release, and resolving debates with demonstrations.
  • Assign human judgment to intent, design, and risk; use automated checks and agent reviewers to verify code; expand autonomous releases as safeguards prove reliable while retaining human control over irreversible or sensitive decisions.
  • Build evaluations and verification to establish that agents correctly handle known use cases and continue to do so as systems change.
  • Coordinate a team across New York, California, Spain, and India with written hand-offs, open decision-making, and sufficient overlap for working relationships.

Desired Qualifications

  • Built or led engineering for agent products and understand how to make non-deterministic systems dependable.
  • Designed evaluations or automated verification for agent behavior and detected regressions before customers did.
  • Built internal agent tooling or an automated delivery pipeline that replaced manual work.
  • Experience with formal or rigorous specification and verification methods.
  • Served as a founder or early engineering leader at a startup that shipped a real product under real constraints.

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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