About the work

This position is on our Applied AI team, which is responsible for helping Honor safely and pragmatically apply AI across our operating model, product systems, and internal workflows.

The mission of the Applied AI team is to help Honor become an organization that learns faster, remembers more, and continuously compounds what it learns over time. We believe the most valuable use of AI at Honor is not isolated task automation, but building durable organizational intelligence: systems that retain operational context, surface relevant prior learning, support better decisions, and help teams turn fragmented insights into repeatable improvements.

Honor operates in a deeply relationship-driven industry. The best home care operators personalize service because they remember the details, understand context, and adapt to the situation. At Honor’s scale, that requires thoughtful systems: reliable context, governed access, reusable AI patterns, traceable workflows, and product experiences that help humans and agents make better decisions together.

As a Staff Engineer on Applied AI, you will help design, build, and productionize the foundations that make this possible. You may work on systems that power AI-assisted sales follow-up, operational defect analysis, reusable memory and retrieval patterns, internal agentic tools, AI-powered data analysis, schedulable workflows, or closed-loop feedback systems that connect audits, product changes, and measurable business outcomes.

You will work closely with engineering, product, design, data, operations, security, and business stakeholders to move quickly while maintaining the discipline needed for production systems. This team is highly exploratory, but the work is not a lab exercise. We are looking for engineers who can turn ambiguous AI opportunities into safe, reliable, measurable product and platform capabilities.

We have an exciting runway ahead of us. As AI becomes an operational layer across Honor, we need engineers who can help create the paved roads: secure model access, compliant data pathways, observability, cost controls, evaluation patterns, human-in-the-loop workflows, and reusable architecture that allows teams across Honor to adopt AI without creating long-term fragmentation.

About you

• You thrive in a diverse, cross-functional team, collaborating with design, product management, data, operations, security, and other engineering teams.
• You are excited by ambiguous, high-leverage problems where the right answer requires both technical judgment and operational empathy.
• You enjoy building production-grade systems that connect user-facing workflows, backend services, data pipelines, and AI/LLM capabilities.
• You’ve built and maintained production-grade features in Python, or have transferable experience in common languages like Node.js and are willing to learn Python.
• You know how to design reliable data models and have used relational databases at scale.
• You have been a key contributor to the design and implementation of large, complex projects.
• You are comfortable working in and refactoring legacy, monolithic systems while also designing new services and integration patterns.
• You are a strong communicator, both verbally and in writing, and can explain technical tradeoffs to technical and non-technical audiences.
• You think carefully about quality, observability, privacy, security, and operational risk.
• You are excited to work with AI systems in a way that is pragmatic, measurable, and grounded in real business outcomes.
• You are willing to participate in an on-call rotation in collaboration with our tier 1 support team.

Some, or all, of these are true

• You have experience building LLM-powered products, AI agents, retrieval systems, memory systems, or evaluation frameworks.
• You have worked with model providers or platforms such as AWS Bedrock, OpenAI, Gemini, Anthropic, or similar systems.
• You have experience with secure data access patterns, RBAC, auditability, or compliant data workflows.
• You have built internal tools, workflow automation, or systems that support operations teams at scale.
• You are comfortable working with messy operational data and turning it into reliable product or platform capabilities.
• You have experience designing systems that involve human-in-the-loop review, feedback loops, or measurable quality improvement.
• You are knowledgeable about microservice architecture and best practices.
• You have experience working with an RPC architecture.
• You are comfortable with frontend development and have experience with JavaScript frameworks like React.
• You have experience leveraging observability and monitoring tools like DataDog.
• You enjoy mentoring and spreading knowledge to other engineers.
• You are energized by building foundations that help other teams move faster and more safely.

Tech you may use

• Python
• Thrift
• MySQL
• AWS
• AWS Bedrock
• OpenAI, Gemini, Anthropic, or similar model platforms
• JavaScript
• React
• Looker
• GitHub
• DataDog
• Internal agentic tools and workflow automation platforms

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