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About This Role
Thank you for your interest in joining Solventum. Solventum is a new healthcare company with a long legacy of solving big challenges that improve lives and help healthcare professionals perform at their best. At Solventum, people are at the heart of every innovation we pursue. Guided by empathy, insight, and clinical intelligence, we collaborate with the best minds in healthcare to address our customers’ toughest challenges. While we continue updating the Solventum Careers Page and applicant materials, some documents may still reflect legacy branding. Please note that all listed roles are Solventum positions, and our Privacy Policy: https://www.solventum.com/en\-us/home/legal/website\-privacy\-statement/applicant\-privacy/ applies to any personal information you submit. As it was with 3M, at Solventum all qualified applicants will receive consideration for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Job Description:
AI Architect – Modern AI Applications
3M Health Care is now Solventum
At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game\-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue.
We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you.
The Impact You’ll Make in this Role
As a AI Architect with deep expertise in Machine learning, Agentic AI, Generative AI, and Natural Language Understanding (NLU), you will lead high\-impact AI Platform development for HIS applications. In this role, you will be a hands\-on research and development leader \- driving technical breakthroughs, designing novel AI architectures, and directly influencing the integration of advanced AI into mission\-critical healthcare products. You will collaborate closely with other scientists, engineers, and domain experts to create platform/solutions that are explainable, reliable, and transformative for healthcare operations.
This role is focused on building scalable AI platforms and frameworks from scratch and is not a data science or model experimentation role.
Key Responsibilities
Healthcare\-Focused AI Development
- Architect, design and develop AI platform to support large language models to handle healthcare\-specific language, regulatory requirements, and ethical considerations.
- Frameworks which can support AI pipelines that can process structured and unstructured healthcare data (FHIR, HL7, clinical notes, claims data).
- Contribute to domain\-specific model architectures that improve clinical decision\-making, revenue cycle management, and patient engagement.
Technical Leadership
- Serve as the primary technical authority on any AI Platform related development within product teams.
- Mentor junior AI designers and engineers through code reviews, research guidance, and technical workshops.
- Drive internal knowledge\-sharing on emerging AI trends, frameworks, and best practices.
Operational \& Compliance Excellence
- Implement rigorous model evaluation frameworks for accuracy, robustness, and fairness.
- Ensure compliance with healthcare privacy and data security regulations (HIPAA, HITRUST).
- Partner with engineering to move research prototypes into production environments.
Your Skills and Expertise
To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications:
- Master’s in Computer Science, AI, Machine Learning, or related field AND 10\+ years of experience in developing AI/ML platform on Cloud \& on\-Prem.
Or
- 15\+ software engineering background in AI, Machine Learning, or related field with 10\+ years of experience in building AI/ML platforms.
- Proficiency in Python, and modern ML libraries.
- Experience with GenAI, LLMs, transformer architectures, and advanced Model Routing (dynamically selecting and orchestrating open\-source vs. proprietary models based on latency, cost, and capability tiers).
- Skilled with AI development tools and frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex).
- Deep expertise in building enterprise\-grade RAG systems, including advanced chunking, hybrid search, vector database management, and retrieval optimization.
- Hands\-on experience with autonomous AI agents and reasoning systems, specifically mastering Agent\-to\-Agent (A2A) communication protocols and the Model Context Protocol (MCP) for multi\-agent orchestration.
- Advanced skills in Agent Context Management, including context window optimization, stateful memory injection, caching strategies, and managing long\-running agent contexts.
- Proven ability in Observability, Logging, and Scalable systems, including specialized LLM/Agent tracing to monitor reasoning steps, token usage, and system latency.
- Strong track record applying AI architectures to scalable, generic enterprise platforms and complex use cases.
- Strong background with cloud platforms, On\-Prem deployments, and MLOps/LLMOps practices.
Additional qualifications that could help you succeed even further in this role;
- Experience with Knowledge Graph DBs (e.g., Neo4j), NoSQL/SQL databases, and native Vector databases, particularly in designing advanced GraphRAG and hybrid\-retrieval architectures.
- Strong background in containerization and infrastructure as code (Kubernetes, Terraform, etc.).
- Familiarity with advanced multi\-agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel) for complex, stateful workflow execution.
- Proven ability to take complex AI Architecture/Design—especially non\-deterministic LLM and multi\-agent systems—from concept to highly available, production\-grade deployments.
- Experience with LLM Evaluation frameworks (e.g., Ragas, TruLens, LLM\-as\-a\-Judge) to continuously monitor and score agent reasoning and RAG retrieval quality.
- Knowledge of model fine\-tuning techniques (LoRA, PEFT) and model distillation to create smaller, task\-specific models that optimize cost and latency within the model routing layer.
- Familiarity with implementing platform\-wide AI guardrails, prompt injection defenses, and output validation mechanisms.
Work Location
Remote \- US
Travel
May include up to 10% domestic travel
Relocation Assistance
Is not authorized
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).
Supporting Your Well\-being
Solventum offers many programs to help you live your best life – both physically and financially. To ensure competitive pay and benefits, Solventum regularly benchmarks with other companies that are comparable in size and scope.
Onboarding Requirement: To improve the onboarding experience, you will have an opportunity to meet with your manager and other new employees as part of the Solventum new employee orientation. As a result, new employees hired for this position will be required to travel to a designated company location for on\-site onboarding during their initial days of employment. Travel arrangements and related expenses will be coordinated and paid for by the company in accordance with its travel policy. Applies to new hires with a start date of October 1st 2025 or later.
Applicable to US Applicants Only:The expected compensation range for this position is $184,400 \- $253,550, which includes base pay plus variable incentive pay, if eligible. This range represents a good faith estimate for this position. The specific compensation offered to a candidate may vary based on factors including, but not limited to, the candidate’s relevant knowledge, training, skills, work location, and/or experience. In addition, this position may be eligible for a range of benefits (e.g., Medical, Dental \& Vision, Health Savings Accounts, Health Care \& Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits, etc.). Additional information is available at: https://www.solventum.com/en\-us/home/our\-company/careers/\#Total\-Rewards
Responsibilities of this position include that corporate policies, procedures and security standards are complied with while performing assigned duties.
Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers.
Please note that all email communications from Solventum regarding job opportunities with the company will be from an email with a domain of @solventum.com. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains.
Please note, Solventum does not expect candidates in this position to perform work in the unincorporated areas of Los Angeles County.
Solventum is an equal opportunity employer. Solventum will not discriminate against any applicant for employment on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.Please note: your application may not be considered if you do not provide your education and work history, either by: 1\) uploading a resume, or 2\) entering the information into the application fields directly.
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Salary Context
This $184K-$253K range is above the 75th percentile for AI Architect roles in our dataset (median: $181K across 29 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 4,317 AI roles we're tracking, AI Architect positions make up 1% of the market. At Solventum, 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 $237,300 based on 102 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($218K) sits 8% below the category median. Disclosed range: $184K to $253K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Solventum AI Hiring
Solventum has 1 open AI role right now. They're hiring across AI Architect. Based in Pittsburgh, PA, US. Compensation range: $253K - $253K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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