Senior AI Engineer

Reposted 4 Days Ago
2 Locations
In-Office
Mid level
Artificial Intelligence • Information Technology • Software
The Role
The role involves developing LLM-powered AI features, optimizing AI performance, and collaborating on technical architecture and user experience enhancements. Requires strong skills in machine learning and AI integration.
Summary Generated by Built In
About AirOps

AirOps is the first end-to-end content engineering platform built for the AI era. In a world where discovery is shifting from traditional search to AI-driven platforms, we help brands get found—and stay found. We are currently in a phase of hyper-growth, having 5x’d our revenue in the last year by helping marketing teams at Ramp, Chime, Carta, and Rippling turn content quality into a durable competitive advantage.

Our platform equips marketers to navigate the new discovery landscape, prioritize high-impact opportunities, and create accurate, on-brand content that earns citations from AI and trust from humans. Backed by Greylock, Unusual Ventures, Wing VC, and Founder Collective, we are building the intelligent systems that will empower the next generation of marketing leaders. AirOps is headquartered in San Francisco, New York and Montevideo.

About the Role

We're looking for a product-minded AI engineer to help us rapidly define and ship features that make all AirOps customers 10x content engineers.

In this role, you'll drive the development of advanced AI systems, including our SEO Strategy Agent and Workflow Builder Copilot. You'll lead the creation of intelligent solutions that empower businesses to optimize their SEO strategy and streamline workflow creation with AI-powered assistance.

Joining at a critical juncture, you'll collaborate closely with product management to shape our AI roadmap and technical architecture.

Responsibilities
  • Develop and integrate LLM-powered features such as AI-assisted workflow automation, code generation, and content strategy.

  • Optimize AI performance through prompt engineering, retrieval-augmented generation (RAG), and evaluation frameworks.

  • Build and scale AI infrastructure, ensuring low-latency responses, caching, and cost-efficient model usage.

  • Implement AI observability and safeguards, monitoring quality, security, and compliance.

  • Collaborate with product and engineering teams to deliver intuitive, AI-driven user experiences.

  • Stay ahead of AI advancements, continuously improving our AI-powered capabilities.

  • Collaborate with early adopters to optimize model performance and usability.

Qualifications
  • 3+ years of experience in machine learning engineering, AI/LLM integration, or applied NLP

  • Proven track record of building LLM-powered applications

  • Strong experience with foundation models (GPT-4o, Claude, etc.) and advanced prompt engineering

  • Experience with embedding models (e.g., OpenAI Ada, Cohere, or local vector stores like pgvector, Weaviate, Pinecone)

  • Deep understanding of retrieval-augmented generation (RAG) and contextual AI response optimization

  • Familiarity with LangChain, or similar frameworks for orchestrating LLM-powered applications

  • Strong programming skills in Python (experience with AI frameworks like Hugging Face, LangChain, or OpenAI SDK)

  • Experience in evaluating LLM performance, running A/B tests, and implementing feedback loops for AI refinement

  • Solid understanding of caching, rate limiting, and cost optimization strategies for AI workloads

  • Ability to work cross-functionally with engineers, product managers, and end users to develop impactful AI solutions

Our Guiding Principles
  1. Extreme Ownership

  2. Quality

  3. Curiosity and Play

  4. Make Our Customers Heroes

  5. Respectful Candor

Benefits
  • Equity in a fast-growing startup

  • Competitive benefits package tailored to your location

  • Flexible time off policy

  • Parental Leave

  • A fun-loving and (just a bit) nerdy team that loves to move fast!

Skills Required

  • 3+ years of experience in machine learning engineering, AI/LLM integration, or applied NLP
  • Proven track record of building LLM-powered applications
  • Strong experience with foundation models (GPT-4, Claude, etc.) and advanced prompt engineering
  • Experience with embedding models (e.g., OpenAI Ada, Cohere)
  • Deep understanding of retrieval-augmented generation (RAG)
  • Familiarity with LangChain for orchestrating LLM applications
  • Strong programming skills in Python
  • Experience in evaluating LLM performance and implementing feedback loops
  • Solid understanding of caching, rate limiting, and cost optimization for AI workloads
  • Ability to work cross-functionally with engineers and product managers

AirOps Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AirOps and has not been reviewed or approved by AirOps.

  • Healthcare Strength Healthcare coverage is described as fully covered across medical, dental, and vision, minimizing out-of-pocket costs for employees. Feedback suggests this level of coverage is a standout element of the total rewards.
  • Leave & Time Off Breadth Time-off provisions include unlimited PTO alongside generous parental and family leave, supporting flexibility during both everyday and major life events. Feedback suggests these policies enhance work-life balance.
  • Equity Value & Accessibility Equity is consistently included across roles and positioned as a meaningful component of total compensation in a fast-growing startup context. Feedback suggests this upside strengthens overall pay perception.

AirOps Insights

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The Company
HQ: San Francisco, CA
57 Employees
Year Founded: 2021

What We Do

Build your AI growth engine. AirOps lets you easily build and scale AI workflows to crush your growth targets. Build with 40+ AI models, retrieval, and data sources or launch one of our proven playbooks.

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