Vaco is partnering with a growing education technology organization to hire a Staff / Principal AI Engineer to help define and build the next generation of AI-powered products, platforms, and internal capabilities. This is a highly visible, hands-on technical leadership role focused on bringing practical AI innovation into both customer-facing products and internal business operations.
This person will serve as a technical change leader as the organization moves toward broader use of AI agents, generative AI, machine learning, and LLM-powered product experiences. The right candidate will bring strong architecture and engineering depth, but also a product mindset. This role is about building real solutions, teaching teams how to use AI effectively, securing AI-enabled workflows, and identifying where AI can improve customer experience, training products, marketing funnels, and business outcomes.
What You’ll Be Doing
- Lead the design, development, and deployment of scalable AI and machine learning solutions across product and internal business use cases
- Architect generative AI systems, LLM-powered workflows, agentic solutions, and AI-enabled product features
- Build and optimize LLMOps pipelines that support reliable deployment, evaluation, monitoring, and iteration of AI models
- Partner with product, architecture, data, engineering, innovation, and marketing teams to identify where AI can create measurable business impact
- Drive AI innovation within customer-facing products, training platforms, digital experiences, and lead conversion workflows
- Evaluate and implement approaches for prompt engineering, context management, embeddings, retrieval, and model optimization
- Design AI systems with feedback loops, automated retraining, fine-tuning, and lifecycle management where appropriate
- Build data pipelines and preprocessing workflows that ensure data quality, security, and regulatory alignment
- Provide hands-on technical leadership through architecture reviews, code contributions, proof-of-concepts, and implementation guidance
- Mentor AI engineers and partner with architects across application, product, CRM, and data domains
- Help establish standards, documentation, and best practices for responsible AI development and deployment
- Stay current on emerging AI trends, including AI’s impact on digital marketing, Answer Engine Optimization, Generative Engine Optimization, and customer discovery behavior
Required Experience
- 8 or more years of progressive experience across software engineering, data, analytics, machine learning, AI engineering, or related technology roles
- 1 or more years of experience developing and implementing analytical, AI, or machine learning applications
- Hands-on experience building and deploying LLM-based solutions, generative AI applications, or AI-powered product features
- Strong understanding of machine learning, natural language processing, large language models, embeddings, retrieval patterns, and model evaluation
- Experience with Python, SQL, Hugging Face, Snowflake, and modern ML or analytics tooling
- Experience designing AI or ML solutions in Azure or comparable cloud environments
- Experience with CI/CD pipelines, Docker, Kubernetes, MLflow, or similar MLOps and lifecycle management tools
- Ability to translate ambiguous AI opportunities into practical, scalable engineering solutions
- Strong product mindset with interest in customer experience, product innovation, marketing enablement, and business impact
- Demonstrated ability to mentor engineers, influence technical direction, and guide best practices
- Strong communication skills with the ability to present complex AI concepts to technical and non-technical stakeholders
- Bachelor’s degree in Computer Science, Artificial Intelligence, or a related field preferred, or equivalent professional experience
Nice to Have
- Experience building AI agents or agentic workflows for internal business operations
- Exposure to AI security, responsible AI, model governance, or securing AI-enabled systems
- Experience applying AI to online shopping, customer acquisition, digital marketing, or lead conversion workflows
- Familiarity with Answer Engine Optimization or Generative Engine Optimization concepts
- Experience with Azure AI services or comparable cloud AI platforms
- Background working in education technology, training platforms, eCommerce, or digital learning environments
- Experience helping organizations adopt AI tools, workflows, and operating models across multiple teams
Compensation & Benefits
- Salary range: $170,000 to $190,000 annually
- Full-time role with benefits package available
If you are a hands-on AI engineering leader who wants to build practical generative AI systems, shape product innovation, and help an organization move from AI experimentation to real enterprise adoption, we would welcome the opportunity to connect.
Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual’s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company’s 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products.
