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About This Role
Associate Director, AI Architect \- US (Remote)
Position Overview
IKS Health is seeking an AI Architect to lead the design and development of modern, AI‑first applications across web and mobile platforms. This role is ideal for a senior technologist who can work across the full stack and has deep hands‑on experience with React, Node.js, Python, LangGraph, and agentic application architectures.
As an AI Architect, you will shape the technical direction of next‑generation patient access solutions, define architectural patterns, and ensure the delivery of scalable, production‑grade AI systems. This is a high‑impact role for someone who thrives at the intersection of engineering excellence, AI innovation, and product delivery.
Key Accountabilities
AI‑First Architecture \& Application Development
- Architect, build, and maintain AI‑first web and mobile applications using modern frameworks and engineering best practices.
- Lead the development of AI‑powered features using Python, LangGraph, and modern LLM tooling.
- Design and implement agentic workflow applications, including orchestration, tool use, stateful flows, and human‑in‑the‑loop patterns.
- Develop end‑to‑end solutions across the front end, back end, APIs, and cloud infrastructure.
- Write clean, scalable, and maintainable code in TypeScript (Node), JavaScript (React), and Python using established design patterns.
- Optimize applications for speed, scalability, reliability, and long‑term maintainability.
Technical Leadership \& Collaboration
- Work closely with cross‑functional teams to define, design, and ship new features with strong ownership of outcomes.
- Provide architectural guidance, code reviews, and mentorship to engineering teams.
- Partner with clients to lead demos, support rollout discussions, and ensure successful adoption of AI‑powered solutions.
The Ideal Profile
We are seeking a senior‑level engineer with deep architectural expertise and hands‑on experience building AI‑native applications. Ideal candidates will have a strong track record of delivering production‑grade, public‑facing systems and demonstrate strong technical judgment, communication skills, and ownership.
Backgrounds that align well with this role include:
- Senior full‑stack engineers or architects building AI‑powered or agentic applications
- AI engineering or applied ML engineering roles with architectural responsibility
- Experience designing systems using LangGraph or similar orchestration frameworks
- Engineers who have built and shipped commercially successful applications
Experience \& Required Qualifications
- Bachelor’s degree or preferably a Master’s degree with 7\+ years of experience in software engineering, AI engineering, or architecture
- Demonstrable experience building commercially successful, public‑facing applications, ideally AI‑native
- Strong proficiency in React.js, Node.js, and Python required
- Experience working with full stack owning end to end features \- must know all parts of the stack
- Proven experience building production applications with a strong portfolio of work
- Hands‑on experience building AI applications, AI agents, or agentic workflows
- Strong understanding of LangGraph or similar orchestration frameworks
- Strong understanding of document and SQL databases
- Good understanding of GCP and cloud‑native architecture
- Strong problem‑solving skills, communication abilities, and an ownership‑driven mindset
About IKS Health
www.ikshealth.com
IKS Health takes on the administrative, clinical, and operational burdens of healthcare so clinicians can focus on delivering exceptional care. Through pragmatic technology and dedicated experts, IKS enables stronger, financially sustainable healthcare enterprises. The Care Enablement Platform delivers data‑driven value across the care journey, supporting large U.S. health systems with scalable, quality‑driven, cost‑efficient solutions. Founded in 2006, IKS has a global workforce supporting clinician enterprises nationwide.
Compensation and Benefits: The salary range for this position is $140,000 to $160,000 US a year, determined by years of relevant experience, skills, and the specific geographical location where the work is performed. Pay is based on several factors, including but not limited to current market conditions, location, education, work experience, certifications, etc. IKS Health offers a competitive benefits package, including healthcare, 401k, and paid time off (all benefits are subject to eligibility requirements for full\-time employees). IKS Health is an equal opportunity employer and does not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Salary Context
This $140K-$160K range is in the lower quartile for AI Architect roles in our dataset (median: $197K across 33 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 3,708 AI roles we're tracking, AI Architect positions make up 1% of the market. At IKS Health, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $254,798 based on 67 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($150K) sits 41% below the category median. Disclosed range: $140K to $160K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
IKS Health AI Hiring
IKS Health has 1 open AI role right now. They're hiring across AI Architect. Based in Remote, US. Compensation range: $160K - $160K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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