Senior AI Engineer​/AI Platform Developer

We are building a technology-driven healthcare and employment-screening organization operating across drug and diagnostic testing, background checks, employment screening, telehealth, healthcare fulfillment, and 503A/B2B healthcare services.

We are seeking an exceptional Senior AI Engineer / AI Platform Developer who can architect, build, deploy, and continuously improve production-grade AI systems that create measurable business outcomes.

This is not a research-only position and not a role for someone who primarily connects APIs.

We want a builder and owner who understands modern AI architecture, LLMs, agents, data pipelines, APIs, cloud infrastructure, security, evaluation, and enterprise software development—and can turn those capabilities into reliable products used by customers and employees.

• Design and build production-grade AI applications, agents, copilots, and automation systems.
• Architect multi-agent and agentic workflows for complex business processes.
• Build LLM applications using leading commercial and open-source models.
• Develop RAG architectures, vector search, knowledge systems, and enterprise AI search.
• Build structured and unstructured data ingestion pipelines.
• Develop reliable APIs and backend services supporting AI applications.
• Design systems for model routing, tool calling, memory, context management, and orchestration.
• Build AI evaluation, testing, observability, and monitoring frameworks.
• Optimize latency, accuracy, reliability, and AI inference costs.

Develop AI systems capable of automating or augmenting:

• Sales prospecting and lead qualification
• Background and employment-screening workflows
• Compliance review
• Document analysis
• Order processing
• Revenue-cycle workflows
• Financial analysis
• Employee training
• Internal knowledge management
• Executive reporting

The goal is not simply to introduce AI. The goal is to create measurable improvements in revenue, productivity, accuracy, customer experience, and operating leverage.

Work with leadership and business teams to rapidly convert business problems into deployable AI products.

Responsibilities include:

• Technical architecture
• Prototyping
• API integrations
• CI/CD
• Testing
• Monitoring
• Documentation
• Production support

You should be comfortable taking a concept from a whiteboard conversation to a functioning production application.

Build integrations between AI systems and platforms such as:

• Hub Spot
• Shopify
• Woo Commerce
• Background-screening platforms
• Drug-testing systems
• Laboratory systems
• Payment systems
• ERP/accounting platforms
• Internal databases
• Third-party healthcare APIs

Because our businesses operate in regulated environments, this position must build AI with security and compliance in mind.

Responsibilities include:

• Role-based access controls
• Audit logging
• Encryption
• Data isolation
• Human-in-the-loop controls
• Hallucination/error monitoring
• PII/PHI protection
• Vendor and model risk assessment

Experience working around HIPAA, FCRA, SOC 2, healthcare data, employment data, or other regulated environments is highly desirable.

Strong professional experience with:

• Python
• FastAPI, Node.js, or comparable backend frameworks
• REST APIs and webhooks
• SQL and relational databases
• Redis
• Docker
• Git/Git Hub
• Cloud architecture: AWS, Azure, or GCP
• CI/CD
• Production monitoring and observability

Strong experience with modern AI technologies including:

• OpenAI
• Gemini
• Open-source LLMs
• RAG
• Embeddings
• Vector search
• Structured outputs
• Agentic architectures
• AI evaluations
• Fine-tuning where appropriate
• AI guardrails and safety systems

Experience with frameworks such as Lang Graph, Lang Chain, Llama Index, PydanticAI, or equivalent technologies is valuable, but we care more about engineering fundamentals than dependency on a particular framework.

You may have previously worked as a:

• Machine Learning Engineer

You are someone who:

• Ships quickly without sacrificing engineering discipline.
• Can operate with incomplete requirements.
• Thinks from first principles.
• Understands business economics as well as technology.
• Challenges weak technical decisions.
• Measures results instead of simply shipping features.
• Can communicate complex architecture clearly to executives.
• Uses AI aggressively in your own development workflow.
• Has personally built production AI products—not merely demos.

• 7+ years software engineering experience
• 3+ years building ML/AI applications
• Demonstrated production LLM experience
• Strong computer science or engineering fundamentals
• Bachelor's or Master's degree in Computer Science, Engineering, AI, Mathematics, or comparable discipline

Exceptional demonstrated ability can outweigh formal education requirements.

Candidates should be prepared to demonstrate:

• Production AI systems personally designed or built.
• Architecture decisions and tradeoffs.
• AI agents or workflows they have deployed.
• Measurable business impact.
• Code quality and…