AI Solutions Architect

Job Description

AI Solutions Architect & Engagement Lead

JOB Location: Greensboro–Winston-Salem–High Point

About LatentView

LatentView Analytics is a global data analytics and AI solutions company that partners with Fortune 500 and high-growth clients to turn data into competitive advantage. Our teams combine deep technical expertise with business context to ship measurable outcomes — not just models and dashboards — across industries.

Job Description

Serve as the primary face of our team at the client site, acting as a trusted advisor to executive sponsors, business leads, and analytics leaders. In this dual-impact role, you will lead the end-to-end delivery of an enterprise-grade AI platform while actively driving strategic growth, identifying expansion opportunities, and scaling our footprint within the client's ecosystem.

You will bridge the gap between business strategy and technical execution, owning stakeholder management, account growth, team leadership, and the high-level architecture of scalable AI and data solutions built on cloud-native infrastructure (Azure Databricks (Good to have)).

Key Responsibilities

1. Account Growth & Strategic Business Development (Growth & Leadership)

• Identify & Expand Opportunities: Proactively identify new AI, analytics, and data engineering use cases across client business units (e.g., e-commerce, legal, supply chain, digital marketing) to expand our account presence and team footprint.
• Executive Relationship Management: Build and nurture strong relationships with clients, and position our team as the primary strategic AI partner.

2. Client Delivery & Program Leadership

• Risk & Change Management: Proactively identify project risks, manage dependencies, handle scope adjustments, and ensure smooth operational clearance on the ground.
• UAT & Change Management: Facilitate business user walkthroughs, manage change adoption, and secure formal executive sign-offs for platform milestones.

3. High-Level Solution Architecture & Delivery Oversight

• Architectural Guidance: Oversee the strategic design of enterprise AI platforms, ensuring high-level solutions align with client cloud standards (Azure Databricks Lakehouse (Good to have)).
• Data & AI Strategy Oversight: Guide the overall architecture for large-scale data ingestion (PIM/PLM, vendor APIs, heavy unstructured files), governance frameworks, and automated validation pipelines (LLM-as-a-Judge frameworks).
• Cost & Resource Optimization: Establish governance frameworks for AI model spending, token utilization, and infrastructure cost controls for client stakeholders.
• Bridge to Offshore: Translate complex client business requirements into structured deliverables, guiding the offshore engineering pod to execute high-quality solutions on time.

Qualifications & Experience

• Enterprise AI & Data Strategy: Strong architectural knowledge of modern data platforms (Databricks, Lakehouse architecture) and Generative AI patterns (RAG, agentic workflows, multi-model evaluation frameworks).
• Delivery Management & Governance: Demonstrated experience managing end-to-end Agile software delivery, sprint execution, risk escalation, and change management.
• Business Acumen: Ability to translate complex technical concepts into clear business ROI for non-technical executives and brand leaders.
• Technical Background: Prior hands-on experience in data engineering, AI/ML, or enterprise cloud solutions, enabling effective oversight of technical teams and architectural decisions.

Required Skills

• Account Growth & Business Expansion: Proven ability to identify new business opportunities across enterprise client teams to grow current accounts and expand team footprints.
• Client Engagement & Program Delivery: Demonstrated success in leading onsite client engagements, managing executive stakeholders, facilitating sprint planning, and driving program governance.
• Data Platforms & Cloud Ecosystems: Deep understanding of modern cloud data architectures, distributed data processing, enterprise data governance, and scalable storage layers.
• Generative AI & Intelligent Systems: Hands-on experience with LLM orchestration frameworks, retrieval-augmented generation (RAG) patterns, vector databases, and multi-model evaluation pipelines.
• Data Integration & Pipeline Engineering: Strong background in integrating enterprise data sources, master product catalogs, unstructured files, and third-party REST APIs into centralized data environments.
• Software Engineering & Data Analysis: Proficiency in Python, SQL optimization, structured data validation, and building robust API-driven workflows.

Compensation

Base pay range: USD $151,200 – USD $168,300 annually. This range reflects base salary only, excludes Incentive and benefits, and is a good-faith estimate for this level and location that may vary based on experience, skills, and where the role is performed.

Communication

This role requires fluent spoken and written English to communicate directly with client stakeholders, a job-related requirement of the client-facing work itself, not of any candidate's background or origin.