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AI Summary

Lead the design and implementation of an end-to-end AI architecture for a new Tech Risk product focused on SOC reporting. Define AI models, pipelines, and governance frameworks while integrating LLMs and API-driven architectures into enterprise platforms.

Domain AI Azure Architect

AI ARCHITECT to Build a new product for tech risk which will heavily use a.i.

Skills required: be LLM, API, A.I architecture and design expertise.

ASN - SOC Reporting (INV) correct

AI Architect – Tech Risk (ASN – SOC Reporting Product)

Fueled by strategic investment in technology and innovation, Client Technology is focused on driving growth opportunities and solving complex business challenges through the development of robust platforms and next-generation, AI-powered products.

As an AI Architect, you will lead the design and development of a new product within Technology Risk (ASN – SOC Reporting), leveraging advanced Artificial Intelligence, Large Language Models (LLMs), and API-driven architectures.

You will work closely with technologists, data specialists, and business stakeholders, combining deep domain expertise with cutting-edge AI capabilities to deliver scalable, intelligent solutions. This role places you at the forefront of integrating AI into enterprise platforms, enabling smarter automation, analytics, and decision-making.

The Opportunity

Design and implement end-to-end AI architecture for a new product within Tech Risk, focused on SOC reporting and intelligent automation.

Define and govern AI models, pipelines, and infrastructure, ensuring scalability, security, and compliance with enterprise and regulatory standards.

Drive innovation by incorporating LLMs, generative AI, and advanced analytics into product capabilities.

________________________________________

Key Responsibilities

Design and lead AI/ML architecture, including LLM-based solutions, model orchestration, and intelligent workflows

Develop scalable architectures integrating LLMs, APIs, and enterprise systems

Define frameworks for prompt engineering, model fine-tuning, evaluation, and monitoring

Architect end-to-end AI platforms across cloud environments (Azure, AWS, GCP)

Ensure AI solutions align with data privacy, security, and compliance (Tech Risk / SOC requirements)

Collaborate with cross-functional teams to translate business requirements into AI-driven solutions

Design API-first architectures to expose AI capabilities across platforms

Lead the integration of structured and unstructured data into AI pipelines

Establish best practices for AI governance, explainability, and responsible AI

Provide technical leadership in resolving complex architecture challenges

Support product innovation by identifying opportunities to embed automation and intelligence into workflows

Skills and Attributes for Success

AI Architecture & Design

Strong expertise in designing enterprise-grade AI solutions, including LLM integration and generative AI applications

Large Language Models (LLMs)

Experience with GPT-like models, prompt engineering, fine-tuning, embeddings, and vector databases

API & Microservices Architecture

Ability to design scalable API-driven ecosystems for AI services integration

Cloud & AI Platforms

Hands-on experience with Azure AI, AWS AI/ML, or GCP AI services

Data & AI Integration

Understanding of data pipelines, data lakes, and structured/unstructured data processing for AI use cases

Responsible AI & Governance

Knowledge of AI ethics, bias mitigation, model explainability, and compliance standards

Solution Architecture

Ability to design end-to-end enterprise solutions including security, scalability, and performance considerations

To Qualify for the Role, You Must Have

Strong experience in AI/ML architecture and solution design

Proven experience working with LLMs, generative AI, and AI platforms

Experience designing and integrating APIs and microservices

Cloud experience: Azure (preferred), AWS, or GCP

Familiarity with vector databases, embeddings, and semantic search

Understanding of Tech Risk, compliance, or SOC-related processes (preferred)

Experience in distributed systems and scalable architectures

Education

M.S. or B.S. in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field

What We Look For

Strong analytical and problem-solving skills

Innovative mindset with passion for AI and emerging technologies

Ability to lead architecture decisions and influence stakeholders

Excellent communication and collaboration skills

Ownership mindset and ability to drive initiatives independently

High attention to detail and commitment to quality

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