AirOps

1-50

Computer Software

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.

Job Description

About AirOps

Today thousands of leading brands and agencies use AirOps to win the battle for attention with content that both humans and agents love.

We’re building the platform and profession that will empower a million marketers to become modern leaders — not spectators — as AI reshapes how brands reach their audiences.

We’re backed by awesome investors, including Unusual Ventures, Wing VC, Founder Collective, XFund, Village Global, and Alt Capital, and we’re building a world-class team with in-person hubs in San Francisco, New York, and Montevideo, Uruguay.

Role Overview

We're seeking an experienced Solutions Engineering Manager to lead our post-sales technical team. This role sits at the critical intersection of customer success, technical implementation, and business value realization. You'll guide a team of Solutions Engineers who transform client needs into effective AI workflows while continuously improving our service delivery model.

Post-sales technical excellence is a key differentiator for AirOps. Your leadership will ensure customers successfully implement our LLM-powered solutions in ways that drive measurable business impact, leading to stronger retention and expansion opportunities.

Key Responsibilities

Team Leadership & Development

Lead and develop a team of Solutions Engineers focused on post-sales implementation and customer success
Provide technical oversight for complex implementations, ensuring quality and alignment with customer success metrics
Create training materials that empower customers to self-serve where appropriate while identifying opportunities for high-value engagement

AI/LLM Technical Implementation

Design and implement AI/LLM solutions that solve real business problems, with deep understanding of prompt engineering, context handling, and retrieval techniques
Translate complex LLM capabilities into practical workflow implementations that deliver clear ROI
Optimize LLM performance across different use cases, including understanding when to use RAG, fine-tuning, or other techniques

Process & Standards Development

Refine our post-sales playbook, establishing repeatable processes while maintaining flexibility for unique customer needs
Build a library of vertical-specific AI workflows that demonstrate clear ROI and can be efficiently deployed
Establish implementation metrics that balance speed, quality, and customer satisfaction

Cross-Functional Collaboration & Strategy

Partner with Product, Sales, and CX teams to identify common customer challenges and turn them into scalable AI solutions
Bridge technical complexity with business outcomes, ensuring implementations focus on value rather than just technical completion
Identify expansion opportunities within existing accounts based on usage patterns and business needs

Experience & Skills

7+ years of experience in technical customer-facing roles with at least 3 years in management
Strong technical foundation in software implementation, experience in SaaS platforms and workflow automation
Demonstrated success leading post-sales technical teams in a high-growth environment
Proven ability to translate technical capabilities into business value propositions
Track record of improving implementation processes and customer success metrics
Experience with workflow automation tools like Zapier, Make or similar platforms
Excellent communication skills with ability to explain complex technical concepts to various stakeholders
Data-driven approach to measuring implementation success and team performance
Problem-solving mindset with ability to identify root causes of implementation challenges
Coding experience in Python or JavaScript preferred but not required

Nice to Have

Experience with AI/LLM technologies including practical application of prompt engineering, retrieval augmented generation, and AI workflow design
Demonstrated understanding of LLM limitations and how to design solutions that mitigate these challenges

What Sets The Right Candidate Apart

You understand the AI landscape and can effectively navigate the rapidly evolving capabilities of LLMs
You can design AI workflows that balance automation with appropriate human oversight
You're a builder at heart who understands both the technical and business sides of AI implementation
You recognize that successful implementations must be measured by business outcomes, not just technical completion
You can strike the right balance between standardization and customization in AI solutions
You're passionate about AI's potential but pragmatic about how to apply it to real business problems
You have experience transforming technical AI capabilities into repeatable workflow templates
You understand that each vertical has unique needs that require tailored approaches to AI implementation
You can navigate the line between being too technically focused and not technical enough