Principal AI Architect

Elevate Patient Financial Solutions®; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical, Dental & Vision Insurance

401K match

PTO 15 days

7 holidays

Floating holidays

Elevate Day

Pet Insurance

Employee referral bonus

Teamwork culture

Career growth

Job summary

Elevate Patient Financial Solutions is seeking a Principal AI Architect to own the AI function, architecture, and production delivery. This hands-on leader will shape technical strategy, partner with Product, and guide the implementation of AI across the Databricks platform.

The role requires 10+ years in software/data/ML with deep Python/SQL expertise, production-grade AI experience, and a track record of ROI-focused delivery. Growth into Head of AI Engineering is anticipated.

Qualifications

• 10+ years of software, data, or ML engineering with expanding scope.
• Strong Python and SQL skills; able to build, test, and debug AI systems.
• Production experience with LLM agents and retrieval-augmented generation.
• Experience securing AI in regulated or sensitive-data environments.

Responsibilities

• Set the AI technical vision and roadmap with leadership.
• Partner with Product to identify AI opportunities and define feasible solutions.
• Design deterministic vs dynamic components and decide build vs buy.
• Develop and deploy retrieval-augmented generation and knowledge graphs.
• Lead the technical build from design through production and mentor engineers.

Skills

Python

SQL

LLM agents

Knowledge graphs

Retrieval-augmented generation

Cost management

Tools

Databricks

MLflow

Delta tables

Job description

Elevate Patient Financial Solutions

has an exciting opportunity open for a Principal AI Architect.

Job Summary

The Principal AI Architect is a hands-on individual contributor who owns the AI technical function at ElevatePFS, including the technical vision, the architecture, and the quality and cost of the solutions the company builds with AI. The role serves as the company's deepest AI technical authority and reports to the VP, AI & Automation. ElevatePFS is building its AI, automation, and intelligence capabilities in-house on a centralized Databricks data platform. Business and product leaders define the problems worth solving. The Principal AI Architect determines whether AI is the right tool for each problem and, if so, designs the solution, builds it, and runs it in production. Training foundation models from scratch is the only work outside the scope of the role. The position is expected to grow into Head of AI Engineering as the team develops.

Essential Duties And Responsibilities

• Set the technical vision and roadmap for AI with the VP, AI & Automation, giving leadership a clear view of feasibility, value, cost, and risk.
• Partner with the Product delivery team to turn workflow problems and improvement opportunities identified in the field into scoped, feasible AI and application opportunities.
• Decide which parts of each solution should be deterministic (rules, parsers, schema validation, SQL, classical ML) and which should be dynamic (LLM reasoning, agentic tool use), using LLMs where inputs are ambiguous and plain code elsewhere.
• Recommend build versus buy and closed versus open models for each solution, and track new models and tooling.
• Design single-agent and multi-agent systems, including routing, planner/executor patterns, tool calling and MCP, state and memory, durable execution, retries, idempotency, human approval gates, and tool permission scoping.
• Define with Product what the application needs to support AI in daily use, such as changed screens, wizards, intelligent interfaces, and approval steps.
• Build and tune retrieval-augmented generation end to end, including parsing, chunking, embedding selection and fine-tuning, hybrid search, reranking, query rewriting, vector search with Delta index sync, and grounded citations.
• Build knowledge graphs and ontology-driven retrieval, including entity resolution and GraphRAG-style hybrids, in partnership with the Data organization.
• Develop document intelligence for contracts, payment files, and correspondence, including OCR, layout-aware parsing, table and field extraction, and multimodal models.
• Design the Databricks data layout that AI depends on, including medallion architecture, Delta table design, liquid clustering, Change Data Feed, Unity Catalog governance and lineage, and feature and serving tables.
• Select models by task, accuracy, latency, cost, and data-handling constraints, fine-tune where it pays off (SFT, LoRA/QLoRA, preference tuning), and distill into smaller, lower-cost models.
• Deploy and serve models on Databricks Model Serving and self-hosted inference such as vLLM, and manage the lifecycle in MLflow, including tracking, tracing, registry, release management, and CI/CD for models, prompts, and agents with shadow, canary, and A/B rollouts.
• Build evaluation and monitoring tied to business outcomes, including golden datasets, field-level precision, recall, and F1, retrieval metrics, groundedness, LLM-as-judge calibrated to human labels, release-gating regression suites, and production drift and agent-trace monitoring.
• Own token and compute spend through routing and cascading, prompt and semantic caching, context compression, batch inference, smaller models, an AI gateway, and cost attribution per agent and workflow.
• Measure ROI and adoption for every AI initiative and recommend whether to scale, rework, or retire it.
• Defend against prompt injection, tool-based data exfiltration, and over-permissioned agents through least privilege, guardrails, PII/PHI redaction, and full audit logging.
• Work with the AI Center of Excellence, Information Security, Compliance, and Legal on model approval and data-handling standards, including standards for PHI.
• Lead the technical build from design through production, write the specs, patterns, and standards for everyone building AI at ElevatePFS, and review code, prompts, and evaluations from employees, contractors, and vendors.
• Hand off completed designs to the Product delivery team, who own implementation and adoption, and provide the specs and guidance they need.
• Keep the intelligence the company builds documented, understood, and owned internally.
• Mentor engineers, help recruit the AI engineering team that forms around the role, and explain technical tradeoffs clearly to executives.
• Other duties as assigned.

Qualifications And Requirements

• 10+ years of experience in software, data, or ML engineering, including 7+ years in machine learning with increasing scope.
• Strong current Python and SQL skills, with the ability to build, test, and debug AI systems personally.
• Production experience with LLM agents, retrieval-augmented generation, knowledge graphs, closed and open-weight models, fine-tuning, and model deployment.
• Record of proving ROI, controlling AI cost, and choosing well between deterministic and LLM-driven design.
• Experience securing AI systems in regulated or sensitive-data environments.
• Record of setting technical direction that others executed, including across employees, contractors, and vendors.
• Preferred: Healthcare, healthcare IT, or revenue cycle management background, including HIPAA and PHI-compliant AI deployment.
• Preferred: Knowledge graph or ontology experience, and document intelligence or claims and contract extraction experience.
• Preferred: Deep Databricks and MLflow experience, including Delta, Unity Catalog, Model Serving, and Vector Search.
• Preferred: Azure, event-driven architecture, and workflow automation or RPA experience.
• Preferred: Experience standing up an AI Center of Excellence or internal AI platform.

Benefits

• Medical, Dental & Vision Insurance
• 401K (100% match for the first 3% & 50% match for the next 2%)
• 15 days of PTO
• 7 paid Holidays
• 2 Floating holidays
• 1 Elevate Day (floating holiday)
• Pet Insurance
• Employee referral bonus program
• Teamwork: We believe in teamwork and having fun together
• Career Growth: Gain great experience to promote to higher roles

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training. This pay scale is not a promise of a particular wage.

The job description does not constitute an employment agreement between the employer and Employee and is subject to change by the employer as the needs of the employer and requirements of the job change.

ElevatePFS is an Equal Opportunity Employer