AI Architect

Monotype•Woburn, MA

3d•$130,000 - $155,000•Hybrid

About The Position

Monotype is seeking a Sr. AI Architect to help modernize its 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.

Requirements

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

Nice To Haves

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

Responsibilities

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

Benefits

Hybrid work arrangements
Competitive paid time off programs
Comprehensive commercial medical insurance coverage
Competitive compensation with corporate bonus program
Uncapped commission for quota-carrying Sales (Note: This seems specific to sales roles, but is listed)
Reward & Recognition Programs (including President's Club for all functions)
Professional onboarding program
Robust targeted training for Sales function (Note: This seems specific to sales roles, but is listed)
Development and advancement opportunities (high internal mobility across organization)
Retirement planning options