About KidKare

The people who care for and feed children every day have enough on their plates. Their software shouldn't add to it.

For more than 30 years, KidKare has built technology for the people behind childcare and child nutrition, helping them spend less time on paperwork, compliance, and administrative work and more time focused on the children and communities they serve.

Our roots run deep in the Child and Adult Care Food Program (CACFP), a federal nutrition program that helps provide healthy meals and snacks to children and adults across the country. Today, we're building on that expertise with a growing ecosystem of software supporting childcare organizations across food program compliance, business management, career development, and licensing.

We have a much bigger vision for what we can do across the childcare community with a strong plan focused on bringing more value to customers through new features, modules, and products. To support these goals, we're looking for an AI Engineer to embed within one of our mature, deeply configurable platforms that has real functional and technical complexity built up over years of customer-driven development.

Position Summary

You'll be working inside a legacy codebase with established architecture, business rules, and customer commitments, and your job is twofold:

(1) use AI tooling to extend and modernize what these platforms can do, and

(2) use that same AI expertise to make our existing engineering teams faster and sharper — compressing the time between a customer requirement and a shipped, correct solution.

You will work directly with engineering leads, product, and operators to find where AI-assisted development — code generation,



automated testing, requirement-to-implementation acceleration, intelligent tooling — can shorten delivery cycles without sacrificing quality, especially under aggressive customer timelines.

If you enjoy going deep into complex, configurable systems and making both the product and the team around it faster, this role is for you.

Your mission: use AI to multiply the output and accuracy of our development teams, while extending the intelligence of the platforms themselves.

Primary Responsibilities

Accelerate team delivery

- Introduce and operationalize AI-assisted development practices (code generation, AI pair-programming, automated test generation) across existing engineering teams.
- Identify friction points in how requirements move from customer ask to shipped feature, and apply AI tooling to close the gap.
- Partner with developers working in Angular, React, C#, and TypeScript to embed AI tooling into their actual day-to-day workflow — not a side project.
- Build reusable patterns/playbooks so AI-assisted delivery scales across teams, not just your own output.

Extend platform intelligence

- Design, develop, and deploy AI features directly into existing, deeply configurable SaaS platforms.




- Integrate LLMs and ML models into legacy architectures without destabilizing existing functional/technical requirements.
- Build automation pipelines that reduce manual operational tasks within the product and internally.
- Develop intelligent agents and AI-powered workflow systems where they create measurable leverage.

Architect AI Infrastructure

- Implement RAG systems and embedding pipelines.
- Work with vector databases and retrieval systems.
- Build AI orchestration layers and agent frameworks.
- Ensure reliability, monitoring, and evaluation of AI outputs.
- Deploy and maintain models in production environments.

Collaborate cross-functionally

- Work directly with engineering leads and non-technical stakeholders to understand both platform constraints and business pain points.
- Translate ambiguous problems — in the product or in the development process — into scalable AI solutions.
- Balance speed with engineering rigor, especially against aggressive customer-driven timelines.
- Drive execution with minimal oversight.

Required Technical Skills

Core engineering

- Experience working within deeply configurable, enterprise-grade SaaS platforms (not greenfield products).
- Strong Python expertise (required).
- Comfortable across multiple languages/frameworks — Angular, React, C#, and TypeScript.
- Backend development experience (APIs, microservices) in a mature production codebase.
- Experience deploying production systems; familiarity with cloud infrastructure (AWS, Azure, or GCP).
- CI/CD, Docker, containerization.

AI & ML systems

Experience with:

- LLM integration (OpenAI, Anthropic, open-source models, etc.)
- AI-assisted development tool

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