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About This Role
Andersen is hiring a Lead Enterprise AI Architect for a project defining enterprise AI strategy, scalable architecture, and digital transformation for a healthcare organization.
The customer is a global consulting and advisory firm that helps organizations improve business performance, navigate complex operational challenges, and support strategic transformation. It provides expertise across business strategy, operational improvement, risk management, and organizational change, working with clients from multiple industries through data\-driven insights and multidisciplinary consulting services.
The project is focused on defining the enterprise AI architecture and transformation strategy for a large\-scale healthcare organization. It includes developing a future\-state technical vision, establishing architectural standards, and creating a scalable implementation roadmap to enable secure, enterprise\-wide AI adoption.
Responsibilities:
- Leading the development of enterprise AI architecture and future\-state technical vision.
- Assessing the client's current technology landscape and identifying opportunities to enable enterprise AI capabilities.
- Developing reference architectures supporting generative AI, intelligent automation, enterprise search, document intelligence, and decision support.
- Defining scalable architectural patterns leveraging Microsoft Azure, Azure OpenAI, Retrieval Augmented Generation (RAG), and modern AI technologies.
- Developing solution architectures that align business objectives with technical capabilities.
- Defining implementation of sequencing, technical dependencies, and architectural decision points across multiple workstreams.
- Evaluating technology platforms and providing recommendations supporting future implementation.
- Producing architecture documentation, technical standards, and implementation of roadmaps.
- Presenting architectural recommendations to executive leadership and steering committees.
- Facilitating architecture workshops with business and technical stakeholders.
- Translating complex technical concepts into business\-focused recommendations.
- Supporting executive decision\-making through technology assessments and option analysis.
- Defining enterprise AI governance principles, including responsible AI, security, compliance, privacy, and model lifecycle considerations.
- Establishing architectural standards and reusable design patterns.
- Recommending governance processes that enable scalable AI adoption within a regulated healthcare environment.
- Partnering with Data Architects, Platform Architects, business leaders, and client stakeholders throughout the engagement.
- Supporting the development of integrated recommendations across technology, data, governance, and operating model workstreams.
- Mentoring project teams and providing architectural leadership throughout the engagement lifecycle.
Must\-haves:
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent professional experience.
- Enterprise solution architecture experience for 10\+ years.
- Experience developing enterprise AI or machine learning architectures for 5\+ years.
- Extensive experience with Microsoft Azure cloud architecture.
- Hands\-on experience with Azure OpenAI Service and OpenAI APIs.
- Deep understanding of Retrieval\-Augmented Generation (RAG) architectures.
- Experience developing enterprise AI governance frameworks.
- Strong executive communication and presentation skills.
- Experience advising healthcare organizations or other highly regulated industries.
- Demonstrated success leading enterprise architecture initiatives within consulting or professional services environments.
- Level of English – from Upper\-Intermediate\+ and above.
Nice\-to\-haves:
- Experience with Epic and Microsoft Fabric.
- Experience with LangGraph, Model Context Protocol (MCP), or other agentic AI frameworks.
- Knowledge of healthcare interoperability standards, including FHIR and HL7\.
Reasons why this job would be interesting to you:
- Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson \& Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T\-Systems, etc..
- The opportunity to change the project and/or develop expertise in an interesting business domain.
- Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
- Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
- The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
- Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
- Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
- Certification compensation (AWS, PMP, etc).
- Referral program.
- Private health insurance and compensation for sports activities.
Join us!
Pay: $120,000\.00 \- $135,000\.00 per year
Benefits:
- Employee discount
- Flexible schedule
- Life insurance
- Paid time off
- Referral program
- Tuition reimbursement
Work Location: Remote
Salary Context
This $120K-$135K 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 Andersen, 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($127K) sits 50% below the category median. Disclosed range: $120K to $135K.
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.
Andersen AI Hiring
Andersen has 1 open AI role right now. They're hiring across AI Architect. Based in Remote, US. Compensation range: $135K - $135K.
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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