Senior AI Developer – Architect

Health Admins

. Own AI architecture across cloud platforms (AWS Bedrock, Google Vertex AI)—you'll make the calls on what we build and how .

Posted 6/10/2026full-timeRemote • Texas • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudGraphQLPythonReactTypeScript

About the role

Key responsibilities & impact

Own AI architecture across cloud platforms (AWS Bedrock, Google Vertex AI)—you'll make the calls on what we build and how
Design RAG systems end-to-end, from document ingestion and chunking strategy through retrieval optimization and generation quality
Build agentic systems using modern patterns: MCP (Model Context Protocol), tool-use, function calling, and orchestration frameworks like LangGraph
Define observability and evaluation so we know our AI is actually working in production—not just demo-ing well
Manage cost at scale—model selection tradeoffs, token economics, and budget forecasting as we grow
Establish guardrails and compliance patterns, particularly for healthcare data and HIPAA requirements
Mentor and guide implementation-level developers as the team grows
Ship production systems—this isn't a strategy-only role; you'll write code and deploy real solutions

Requirements

What you’ll need

Bachelor's degree in Computer Science, Data Science, Engineering, or related field; or equivalent practical experience
5+ years in AI/ML development
2+ years in architectural leadership or technical lead roles
Proven track record architecting and deploying AI/ML systems in production environments
Experience designing systems that handle sensitive data with appropriate security and compliance controls
Preferred: Master's degree in Computer Science, AI/ML, or related field
Experience in HIPAA-regulated environments
Insurance or healthcare payer industry experience
Experience building and leading AI/ML teams
Technical Knowledge Required: Deep expertise in AWS Bedrock and/or Google Vertex AI
Proficiency with large language models (Claude, GPT, Gemini) and their APIs
Hands-on experience building RAG systems end-to-end— including document ingestion, parsing, chunking strategies, embedding models, vector databases, and retrieval optimization
Experience with vector databases (Pinecone, pgvector, or similar)
Strong background in prompt engineering and LLM integration patterns
Hands-on experience with agentic patterns: MCP (Model Context Protocol), tool-use/function calling, ReAct, Plan-and-Execute, or similar approaches
Experience with orchestration frameworks (LangGraph, LangChain, or similar)
Experience designing and implementing AI observability and evaluation systems
Track record of managing AI infrastructure costs and optimizing token economics
Proficiency in Python and/or TypeScript for AI/ML development
Experience designing secure, scalable API ecosystems (REST, GraphQL)
Preferred: Experience with LLM Ops tooling (LangSmith, Weights & Biases, Arize, Helicone, or similar)
Familiarity with HIPAA compliance frameworks and PHI data handling requirements
Experience with CI/CD pipelines for ML systems
Knowledge of data governance and lineage tracking

Benefits

Comp & perks

Competitive salary and benefits package
Dynamic and innovative work environment
Opportunities for professional growth and development
Remote work flexibility

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI architectureAWS BedrockGoogle Vertex AIRAG systemslarge language modelsPythonTypeScriptAPI ecosystemsvector databasesprompt engineering

Soft Skills

mentoringleadershipcommunicationteam managementproblem-solvingstrategic thinkingcollaborationevaluationcost managementcompliance awareness

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer ScienceAI/ML certifications