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About This Role
*Woburn, MA*
*Are you our “TYPE”?*
*Named "One of the Most Innovative Companies in Design'' by Fast Company, Monotype brings brands to life through type and technology that consumers engage with every day. The company's rich legacy includes a library that can be traced back hundreds of years, featuring famed typefaces like Helvetica, Futura, Times NewRomanand more. Monotype specializes in the design, development, licensing, and management of typefaces and font technologies for the world’s biggest global brands and individual creative professionals, offering a wide set of solutions that make it easier for them to do what they do best: design beautiful brand* *experiences.*
*Want to learn more about who we are, what we do, and how you can become part of our team of over 1,000 talented employees across the globe? Visit us at*www.monotype.com*.*
We are seeking a Sr. AI Architect to help modernize our technology foundation for AI and enable scalable, secure, enterprise\-grade adoption of AI across the organization. In this role, you will lead the design and evolution of the infrastructure, platforms, patterns, and governance needed to support AI\-enabled products, workflows, automations, and agentic systems. You will work closely with Engineering, IT, Security, Data, Enterprise Systems, and business stakeholders to ensure the company has the right architecture to support modern AI use cases — including LLM applications, retrieval\-augmented generation, AI agents, enterprise knowledge systems, automation platforms, and secure integrations across internal systems.
This is a senior, highly cross\-functional technical leadership role for someone who can bridge enterprise architecture, cloud infrastructure, AI platforms, data systems, security, and practical business enablement. The ideal candidate is both strategic and hands\-on: able to define the roadmap, establish standards, evaluate emerging technologies, and partner with teams to bring scalable AI capabilities into production.
Whatyou’llbe doing:
- Lead the design of the company’s enterprise AI infrastructure and architecture
- Modernize our technology foundation so teams can build and scale AI\-enabled tools, automations, and agentic workflows
- Define common patterns, standards, and best practices for AI applications, integrations, retrieval, governance, and monitoring
- Partner with Engineering, IT, Security, Data, and business teams to identify the platforms and capabilities needed to support AI adoption
- Design scalable approaches for connecting AI systems to enterprise data, knowledge sources, and business applications
- Guide the implementation of secure and reliable AI capabilities, including LLM access, RAG, agent orchestration, observability, and cost management
- Evaluate emerging AI platforms and tools and recommend pragmatic solutions based on business value, scalability, security, and risk
- Provide technical leadership and architectural guidance to teams building AI automations, workflows, and internal AI solutions
- Help shape the enterprise AI roadmap and prioritize foundational investments needed for long\-term success
Whatwe’relooking for:
- 8\+ years of experience in software engineering, cloud infrastructure, enterprise architecture, platform engineering, data engineering, or a related technical field
- Experience with LLMOps, MLOps, platform engineering, or internal developer platforms
- Experience designing or modernizing enterprise\-scale technology platforms, cloud systems, data platforms, or integration architectures
- Strong understanding of AI infrastructure concepts, including LLM platforms, RAG, data retrieval, orchestration, APIs, monitoring, and governance
- Hands\-on experience with cloud platforms and modern AI tools such as Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI, Anthropic, or similar technologies
- Familiarity with orchestration and agent frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, IBM Watson X, AWS AgentCore, or similar technologies
- Experience with vector databases or search platforms such as Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, OpenSearch, or Azure AI Search
- Experience with automation and integration platforms such as Workato, MuleSoft, Boomi, UiPath, n8n, Zapier, Make, or similar tools
- Experience defining AI governance, responsible AI standards, model evaluation practices, or enterprise AI risk frameworks
- Experience integrating enterprise systems, data sources, and SaaS platforms in a secure and scalable way
- Strong understanding of security, privacy, access control, data governance, and compliance considerations for enterprise AI
- Ability to evaluate new technologies and translate them into practical recommendations for the business
- Proven ability to lead technical strategy, influence cross\-functional teams, and communicate complex concepts clearly
- Comfortable balancing long\-term architecture with practical, near\-term delivery
Preferred traits
- Strategic systems thinker who can connect long\-term architecture decisions to practical business outcomes
- Hands\-on technologist who is comfortable prototyping, evaluating tools, and guiding implementation
- Comfortable operating in ambiguity and creating structure where standards, platforms, or processes do not yet exist
- Strong technical judgment with the ability to balance innovation, speed, security, scalability, and operational reliability
- Collaborative partner who can work effectively across Engineering, IT, Security, Data, Legal, and business teams
- Pragmatic modernizer who understands that enterprise AI success depends as much on integration, governance, and adoption as it does on model capability
- Curious, experiment\-driven, and committed to staying current as AI infrastructure and agentic technologies rapidly evolve
What’s in it for you:
- *Hybrid work arrangements and competitive paid time off programs.*
- *Comprehensive commercial medical insurance coverage to meet all your healthcare needs.*
- *Competitive compensation with corporate bonus program \& uncapped commission for quota\-carrying Sales*
- *A creative, innovative, and global working environment in the creative and software technology industry*
- *Highly engaged Events Committee to keep work enjoyable.*
- *Reward \& Recognition Programs (including President's Club for all functions)*
- *Professional onboarding program, including robust targeted training for Sales function*
- *Development and advancement opportunities (high internal mobility across organization)*
- *Retirement planning options to save for your future, and so much more!*
*Monotype is an Equal Opportunities Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.*
The US pay range for this position is $130,000\.00 \- $155,000\.00 annual base salary for external candidates with the appropriate level of experience. A corporate bonus will also be offered as part of this role. The final annual base salary offered will be based on location and experience level, and could be less for internal applicants depending upon experience. The job application window for this role is 30 days from the posting date.
\#LI\-DNI
Salary Context
This $130K-$155K range is in the lower quartile for AI Architect roles in our dataset (median: $169K across 31 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 3,823 AI roles we're tracking, AI Architect positions make up 1% of the market. At Monotype, 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 $212,500 based on 108 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($142K) sits 33% below the category median. Disclosed range: $130K to $155K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Monotype AI Hiring
Monotype has 2 open AI roles right now. They're hiring across AI/ML Engineer, AI Architect. Based in Woburn, MA, US. Compensation range: $155K - $155K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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