AI Architect

Primary Skills: Agentic AI, GenAI, RAG

Description:
This is day 1 onsite in Milford, MA. 6 Months Contract-to-Hire

Responsibilities
Define enterprise AI architecture across machine learning, generative AI, automation, and emerging agent-based capabilities
Develop architectural standards, patterns, and reference architectures for AI solutions.
Work alongside engineering, data, security, and business teams to design scalable and secure AI solutions
Establish and evolve AI governance processes, ensuring alignment with enterprise standards and long-term technology strategy
Review AI solution designs and provide architectural guidance throughout delivery.
Establish engineering standards covering code quality, testing, automation, deployment, and operational readiness
Lead proof-of-concepts and technical evaluations of new AI technologies and platforms
Support the development of operational approaches for deploying, monitoring, and maintaining AI solutions in production
Partner with security and governance teams to ensure AI solutions meet regulatory, compliance, and data protection requirements
Promote responsible and secure use of AI across the organization
Provide technical leadership and mentoring within the AI CoE and wider technology community
Stay informed on AI developments and assess their relevance to client

Qualifications:
Bachelor's or Master's degree in a relevant field or equivalent practical experience.
10 years + experience in enterprise, solution, cloud, data, or application architecture roles
Proven experience designing, implementing, or supporting AI, machine learning, or generative AI solutions within an enterprise environment
Strong understanding of modern AI architecture concepts such as RAG, semantic search, vector databases, prompt design, and AI integration patterns
Experience with at least one major cloud platform (AWS, Azure, or Google Cloud Platform)
Understanding of the lifecycle and operational management of AI solutions in production environments
Hands-on experience with Python and common AI/ML tooling
Strong understanding of APIs, distributed systems, microservices, and modern software architecture principles
Experience working with data platforms, data pipelines, and enterprise data architectures
Exposure to agentic AI, AI orchestration frameworks, intelligent automation, or related technologies would be beneficial
Understanding of AI governance, security, risk, and Responsible AI principles.
Strong communication skills and the ability to engage effectively with both technical and non-technical stakeholders
Experience influencing technical direction, facilitating workshops, and mentoring others.