Enterprise AI Architect / AI Platform Architect

Acunor Infotech

San Diego, CA, United States

3 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Application Frameworks Computing Platforms Microsoft Azure Cloud Engineering Cursor (Graphical User Interface Elements) Systems Development Life Cycle Enterprise Search Cloud Platform System GitHub Copilot

+11 more

Large Language Models IT Architecture Event Driven Architecture AI Platforms Enterprise Integration Data Management Machine Learning Operations Virtual Agents Api Design Legacy Systems Microservices

Job description

Enterprise AI Architecture & Platform Strategy

Define enterprise AI platform strategy, target-state architecture, and AI adoption roadmap.
Architect scalable GenAI solutions, AI agents, RAG platforms, enterprise search, intelligent assistants, and automation frameworks.
Design reusable AI platform capabilities including orchestration, evaluation, observability, governance, security, and lifecycle management.

Agentic AI & AI-Enabled SDLC

Design agentic AI architectures supporting autonomous workflows, contextual reasoning, tool usage, and human-in-the-loop execution.
Establish architecture patterns for AI-assisted engineering across requirements, design, development, testing, deployment, and documentation.
Guide responsible adoption of tools such as Cursor, Claude Code, GitHub Copilot, OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Google Gemini.

Modernization & Enterprise Integration

Lead modernization strategy using API-first, microservices-based, cloud-native, and event-driven architecture patterns.
Design integration frameworks connecting legacy platforms, modern applications, AI services, data platforms, and enterprise workflows.
Establish reusable accelerators, platform standards, governance models, and enterprise architecture patterns.

Leadership & Stakeholder Advisory

Act as a trusted advisor to business, product, engineering, architecture, and executive stakeholders.
Lead architecture workshops, discovery sessions, solution reviews, roadmap planning, and technology strategy discussions.
Translate business goals into practical AI platform roadmaps and executable architecture plans.

Requirements

15+ years of experience in enterprise architecture, AI architecture, platform architecture, product engineering, or technology transformation.
Strong experience designing enterprise-scale AI, GenAI, agentic AI, or intelligent automation platforms.
Deep understanding of LLM applications, AI agents, RAG, enterprise search, orchestration, observability, MLOps/LLMOps, and AI governance.
Strong background in APIs, microservices, enterprise integration, cloud-native platforms, and application modernization.
Experience defining architecture roadmaps, reusable frameworks, platform standards, and modernization accelerators.
Ability to influence executive stakeholders, architecture boards, product teams, and engineering leaders.
Exposure to LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, LlamaIndex, OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Google Gemini is preferred.