Enterprise AI Architect

Orange Business; New Haven (CT); On-site; USD 180,000 - 240,000; Full time

Job summary

Orange Business is seeking an Enterprise AI Architect to design end-to-end AI ecosystems, bridging core infrastructure and AI Knowledge Layer. You will lead architecture for MaaS and GenAI workloads, spanning training, inference, and data pipelines across core, cloud, and edge environments.

The role demands deep expertise in distributed systems, data stacks, and enterprise deployment, with a focus on scalable, globally deliverable services and strong regional leadership for GTM initiatives.

Qualifications

• Architectural expertise in Data & AI Platform Architecture.
• Experience with distributed systems and modern data stacks.
• Architecting for performance, resilience, and scalability in global environments.
• Advanced understanding of AI/ML infrastructure incl. leading models.
• Expertise in database technologies (MongoDB, Snowflake) as foundational components.
• Extensive regional focus and cross-functional team leadership, APAC preferred.

Responsibilities

• Full-Stack AI Architecture Design spanning training, inference, and data pipelines across core, cloud, and edge environments.
• Architect AI Knowledge Layer integrating vector stores and lakehouses to support RAG and enterprise search.
• Define MaaS reference architectures and AI workload placement by latency, resilience, and scale.
• Translate complex AI capabilities into customer-ready solutions and deployable blueprints.
• Collaborate with infrastructure and network teams to align AI platforms with enterprise delivery models.
• Develop enterprise-ready AI frameworks guiding LLM integration into software/workflows.
• Act as architectural anchor for regional GTM initiatives and translate technical AI capabilities into value propositions.

Skills

AI Platform Architecture

Distributed Systems

Data Stack & Lakehouse

LLM Deployment

OpenAI/Anthropic/Google models

MongoDB/Snowflake

Tools

MongoDB

Snowflake

OpenAI APIs

Job description

As anEnterprise AI Architect, you will serve as the primary technical authority for designing and commercializing end-to-end AI ecosystems. This role focuses on bridging the gap between core infrastructure and the high-levelAI Knowledge Layer, ensuring that models, data pipelines, and applications are integrated into repeatable, globally deliverable services. You will lead the architectural strategy for shifting from traditional storage andcomputeto sophisticatedModel AI (MaaS)andAgentic AIframeworks.

Key Responsibilities

• Full-Stack AI Architecture Design:

• Architect comprehensive AI platforms spanningtraining, inference, and data pipelinesacross core, cloud, and edge environments.

• Design theAI Knowledge Layer, integrating object storage, vector databases, andlakehousearchitectures to support RAG (Retrieval-Augmented Generation) and enterprise search.

• Define reference architectures forModel-as-a-Service (MaaS)and the placement of AI workloads based on latency, resilience, and scale.

• Solution Engineering & Service Blueprints:

• Translate complex AI platform capabilities intocustomer-ready solutionsand deployable service blueprints.

• Collaborate with infrastructure and network engineers to ensure AI platforms align with existing enterprise operational and delivery models.

• Developapplication-level AI frameworks, guiding the integration of LLMs into functional enterprise software and workflows.

• Technical GTM & Strategic Leadership:

• Act as thearchitectural anchorfor regional GTM initiatives, translating deep technical AI capabilities into clear value propositions for enterprise customers.

• Guide specialist engineering teams toward integrated outcomes, enabling them to execute confidently innew technologydomains likeGenAI.

• Support high-stakes enterprise pursuits by aligning technical intent with commercial viability and long-term scalability.

Required Qualifications

• Architectural Expertise:

• Proven experience inData & AI Platform Architecture, including deep knowledge of distributed systems and modern data stacks.

• Significant background in architecting forperformance, resilience, and scalabilitywithin global serviceprovideror large enterprise environments.

• AI/ML Domain Knowledge:

• Advanced understanding ofAI/ML infrastructure, including experience with leading models from OpenAI, Anthropic, or Google.

• Expertiseindatabase technologies(e.g., MongoDB, Snowflake) as foundational components for AI solution stacks.

• Strategic Regional Focus:

• Extensive professional history within theAPAC region, managing complex stakeholder environments and cross-functional teams.

• A track recordof driving technical strategy for high-growth business units in the cloud and data sectors.