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Senior Agentic AI Engineer

$194k - $239k

Almaz Capital

Senior Agentic Ai Engineer

Hover helps people design, improve, and protect the properties they love. With proprietary AI built on over a decade of real property data, Hover answers age-old questions like "What will it look like?" and "What will it cost?" Homeowners, contractors, and insurance professionals rely on Hover to get fully measured, accurate, and interactive 3D models of any property — all from a smartphone scan in minutes.

At Hover, we're driven by curiosity, purpose, and a shared commitment to serving our customers, communities, and each other. We believe the best ideas come from diverse perspectives and are proud to cultivate an inclusive, high-performance culture that inspires growth, accountability, and excellence. Backed by leading investors like Google Ventures and Menlo Ventures, and trusted by industry leaders including Travelers, State Farm, and Nationwide — we're redefining how people understand and interact with their spaces.

Hover has one of the richest 3D property datasets on the planet. Millions of structures captured, with sub-inch precision and used by major insurance carriers and construction companies today. The next step is building autonomous systems that can perform inspections, damage assessments, design, and cost estimations with speed, accuracy, and operational trust at scale.

We've already validated the direction. Now we're looking for engineers who want to help build the systems that bring agentic AI into production for real customers.

We're hiring a Senior Agentic AI Engineer to help develop and scale the next generation of autonomous workflows at Hover. This is a highly hands-on role focused on building, testing, and improving production AI systems that operate reliably under real-world conditions. You'll work closely with senior technical leaders, product partners, and fellow engineers to transform ambitious ideas into scalable, customer-facing products.

You'll work at the intersection of:

  • multi-agent orchestration
  • production AI systems
  • evaluation and reliability engineering
  • and enterprise-grade AI trust

If you're excited about solving hard technical problems and building AI systems that customers depend on every day, we'd love to talk to you.

You will contribute by:

  • Building production agentic systems: Design, build, and improve multi-agent workflows, orchestration systems, evaluation frameworks, and reliability mechanisms that power autonomous inspections, damage assessments, and estimation workflows. Help turn validated AI concepts into scalable, customer-facing products.
  • Driving reliability & operational excellence: Develop confidence scoring, observability, testing, and human-in-the-loop systems that improve accuracy, trust, and production performance. Investigate issues, monitor system behavior, and continuously improve reliability at scale.
  • Collaborating across product & engineering: Partner closely with Product, Design, Platform Engineering, and Data Engineering to deliver high-quality AI experiences. Contribute to technical design discussions, translate customer needs into solutions, and help raise the engineering bar through strong execution and collaboration.

Your background includes:

  • 5+ years of software engineering experience building production software systems.
  • Experience building and shipping AI-powered products or systems used by real customers.
  • Strong software engineering fundamentals, including distributed systems, APIs, observability, testing, and debugging.
  • Experience working with LLMs, AI agents, workflow orchestration, retrieval systems, or related AI infrastructure.
  • Ability to reason about reliability, failure modes, and operational tradeoffs in production environments.
  • Strong collaboration and communication skills with both technical and non-technical partners.
  • Curiosity, ownership, and a desire to solve complex problems in ambiguous environments.

Bonus points:

  • Experience building production agentic systems or autonomous workflows.
  • Experience with evaluation frameworks, confidence scoring, or human-in-the-loop systems.
  • Experience in regulated or high-trust domains such as insurance, fintech, healthcare, or legal.
  • Familiarity with AI observability, experimentation platforms, or production ML infrastructure.
  • Experience at a startup or high-growth technology company.

Benefits:

  • Compensation - Competitive salary and meaningful equity in a fast-growing company
  • Healthcare - Comprehensive medical, dental, and vision coverage for you and dependents
  • Paid Time Off - Unlimited and flexible vacation policy
  • Paid Family Leave - We support work/life balance and offer generous paid parental and new child bonding leave
  • Mandatory Self-Care Days - A day set aside each month to allow employees to recharge
  • Remote Wellbeing Resources - We provide recurring fitness classes, meditation/mindfulness tools, virtual therapy, and family planning assistance
  • Learning - We encourage continued education and will help cover the cost of management training, conferences, workshops, or certifications

Hybrid roles at Hover:

Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.

The US base salary range for this full-time position is $194,000 - $239,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Vacancy posted 14 hours ago
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