We are seeking an AI Engineer (Solutions Architect + Applied AI) to design, build, and operate our AI-first technology platforms. This role combines hands-on engineering with high-level architecture ownership and is focused on delivering scalable, secure, and production-grade AI systems across our product and wellness technology platforms.
This is not a narrow ML experimentation role. It is a practical, execution-focused position responsible for ensuring our AI ecosystem is reliable, scalable, and capable of driving measurable real-world impact.
A major focus of this role is agentic AI. You will help design and operate AI agent systems and agent-builder platforms that enable non-programmers across the company to contribute to building technology without needing deep software engineering skills. You will guide architecture, implementation, and operational standards across the full AI stack, from data pipelines to model deployment.
You will work closely with leadership, product, clinical, and engineering teams to translate product vision into production AI systems.
Key Responsibilities
AI Platform Architecture & Infrastructure
- Design and maintain scalable AI-first architecture for multi-tenant B2B2C platforms, APIs, and white-label deployments
- Build and manage event-driven systems, distributed services, and modern data infrastructure
- Work extensively with Azure managed services, serverless infrastructure, and containerized workloads
- Manage vector databases, feature stores, data pipelines, CI/CD, infrastructure-as-code, and identity/secrets systems
- Establish strong operational standards including monitoring, alerting, SLIs, SLOs, and incident runbooks
- Design with scalability, reliability, security, and cost-efficiency in mind
- Use AI-assisted engineering workflows to accelerate design, provisioning, and documentation
Applied AI & ML Systems
- Translate product and clinical use cases into production AI features
- Build systems involving RAG, AI agents, tool-use systems, multimodal AI, and time-series analysis for wearable data
- Manage model evaluation, prompt engineering/versioning, experimentation, testing, and continuous improvement
- Implement pipelines for data labeling, weak supervision, retrieval optimization, and performance monitoring
- Work with modern AI orchestration tools such as LangChain and leading LLM providers including GPT, Claude, Gemini, and Grok
Agentic AI & AI-Driven Development
- Lead development of agentic AI systems and internal agent-builder platforms
- Build AI-driven workflows for coding assistance, automation, configuration, and deployment
- Contribute to AI-enabled SDLC workflows including requirement interpretation, automated testing, regression testing, release validation, and deployment automation
Data Governance, Privacy & Security
- Design systems handling sensitive health and personal data using privacy-by-design principles
- Support policies for PII/PHI handling, consent, traceability, retention, and cross-border compliance
- Support integrations with wearables, EHRs, LIS platforms, and payment systems
- Maintain strong security foundations including encryption, key management, and least-privilege access
Required Skills & Experience
- Strong experience building cloud-based systems and AI-powered products
- 4+ years of TypeScript experience using frameworks such as NextJS and Fastify
- 4+ years of Python experience, especially FastAPI
- Hands-on experience with LangChain, LLM orchestration frameworks, prompt pipelines, and LLMs such as GPT, Claude, Gemini, and Grok
- Experience with Azure services including Azure Container Apps, Azure Functions, Azure PostgreSQL, Cosmos DB, and vector databases such as Qdrant
- Proven experience building AI agents or agentic workflows in production
- Experience with AI-assisted development or code-generation workflows
- Strong understanding of distributed systems, APIs, data infrastructure, and security fundamentals
Application Requirements
- 8–12+ years building cloud-based technology products
- 3+ years as a Tech Lead, Principal Engineer, or Solutions Architect
- Production experience deploying LLMs or AI agents at scale
- Strong systems design capability and experience building reliable production infrastructure
Ideal Candidate
- Full-stack AI engineer with strong systems architecture capability
- Comfortable building production-grade AI platforms
- Highly autonomous and able to own complex technical systems
- Passionate about agentic AI and AI-driven development
- Excited to build technology that enables non-programmers to create with AI
- Thrives in fast-moving, remote, globally distributed teams
Compensation
- Monthly Retainer: USD $1,500–$2,500