AI Solutions Architect

LatentView Analytics Ltd.; Cary (NC); Vor Ort; USD 151.000 - 168.000; Vollzeit

Zusammenfassung

LatentView Analytics is seeking an AI Solutions Architect & Engagement Lead to own the end-to-end delivery of an enterprise AI platform at client sites across Greensboro–Winston-Salem–High Point. You will guide strategy, oversee architecture, and drive growth opportunities with executive sponsors and analytics leaders.

In this role you’ll bridge business strategy and technical execution, manage stakeholders, and lead offshore teams to deliver scalable AI and data solutions on cloud-native

Qualifikationen

• Enterprise AI and data strategy experience with modern data platforms.
• Delivery management and governance in Agile environments.
• Ability to translate tech concepts into business ROI for executives.
• Hands-on background in data engineering, AI/ML, or cloud solutions.

Aufgaben

• Own end-to-end delivery of an enterprise AI platform.
• Manage stakeholder relationships with executives and sponsors.
• Oversee high-level architecture and cloud standards.
• Drive account growth and expansion opportunities.

Kenntnisse

Account Growth

Client Engagement

Data Platforms

Generative AI

Data Integration

Python

Tools

Databricks

Lakehouse

Jobbeschreibung

AI Solutions Architect & Engagement Lead

JOB Location: Greensboro–Winston-Salem–High Point

About LatentView

LatentView Analytics is a global dataanalytics and AI solutions company that partners with Fortune 500 andhigh-growth clients to turn data into competitive advantage. Our teams combinedeep 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 teamat the client site, acting as a trusted advisor to executive sponsors, businessleads, and analytics leaders. In this dual-impact role, you will lead theend-to-end delivery of an enterprise-grade AI platform while actively drivingstrategic growth, identifying expansion opportunities, and scaling ourfootprint within the client’s ecosystem.

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

Key Responsibilities

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

• Identify & Expand Opportunities: Proactively identify new AI, analytics, and data engineering usecases 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, andpositioning our team as the primary strategic AI partner.

2. Client Delivery & Program Leadership

• Risk & Change Management: Proactively identify project risks, manage dependencies, handlescope 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, ensuringhigh-level solutions align with client cloud standards (Azure DatabricksLakehouse(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, andautomated validation pipelines (LLM-as-a-Judge frameworks).
• Cost & Resource Optimization: Establish governance frameworks for AI model spending, tokenutilization, and infrastructure cost controls for client stakeholders.
• Bridge to Offshore: Translate complex client business requirements into structureddeliverables, guiding the offshore engineering pod to execute high-qualitysolutions on time.

Qualifications & Experience

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

Required Skills

• Account Growth & Business Expansion: Proven ability to identify new business opportunities acrossenterprise 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 drivingprogram governance.
• Data Platforms & Cloud Ecosystems: Deep understanding of modern cloud data architectures,distributed data processing, enterprise data governance, and scalable storagelayers.
• Generative AI & Intelligent Systems: Hands-on experience with LLM orchestration frameworks,retrieval-augmented generation (RAG) patterns, vector databases, andmulti-model evaluation pipelines.
• Data Integration & Pipeline Engineering: Strong background in integrating enterprise data sources, masterproduct catalogs, unstructured files, and third-party REST APIs intocentralized data environments.
• Software Engineering & Data Analysis: Proficiency in Python, SQL optimization, structured datavalidation, and building robust API-driven workflows.

Base payrange : USD $151,200 – USD $ 168,300 annually. This range reflects basesalary only — it excludes Incentive and benefits — and is a good-faith estimatefor this level and location that may vary based on experience, skills, andwhere the role is performed.

Communication : Thisrole requires fluent spoken and written English to communicate directly withclient stakeholders — a job-related requirement of the client-facing workitself, not of any candidate's background or origin.