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AI Engagement Lead / Solution Architect - Remote

Aventine softwareUnited States🇺🇸United StatesPosted 15 Jul 2026

Why This Role Stands Out

As an AI Engagement Lead / Solution Architect, you will drive innovative Generative AI projects from concept to full-scale implementation, owning both the technical architecture and client relationships in this fully remote role. This position offers significant growth potential for experienced AI professionals who excel at solution design, technical leadership, and strategic client engagement. Apply now to make a substantial impact and shape the future of AI solutions.

Quick Overview

Work Type
Remote
Level
Mid Senior

Job Description

Role: AI Engagement Lead / Solution Architect

Location: Remote

Type: Fulltime Role

Looking for an AI Engagement Lead / Solution Architect to lead a GenAI engagement end-to-end from POC through full-scale implementation. You will act as the single point of accountability for both the architecture and the delivery: you own the solution design and the key technical decisions, and you lead the client relationship and program to a successful, governed release. You will direct a team of specialists (AI/ML engineers, integration and automation engineers) and partner with the client's own architects, business analysts, and valuation SMEs.

This is an accountable architect-lead role. You are expected to make and own the right design decisions, set the guardrails, and govern delivery leaning on your specialist engineers to build the deep components.
Required skills
10+ years of professional experience, with 4+ years driving Machine Learning / AI projects and solution design.
Accountable ownership of solution architecture able to set the target architecture, make and defend key design decisions, and be answerable for them to the client.
Good working understanding of modern GenAI agentic designs and frameworks (e.g., LangChain / LangGraph) and of AI integration patterns, including MCP (Model Context Protocol)-style tool and data integration.
Ability to define security boundaries and model/tool controls what an AI system is allowed to access and do, guardrails against incorrect or unverifiable outputs, and human-in-the-loop checkpoints.
Experience establishing delivery governance and release gates clear quality, security, and compliance criteria that each release must pass before go-live.
Understanding of Cloud services (Azure, Google Cloud Platform, or AWS) and Agile delivery with tools like JIRA and Confluence.
Excellent communication and stakeholder management to collaborate with senior client SMEs; an entrepreneurial, founder's mindset to own delivery end-to-end.
Good to have: exposure to financial-services / asset-management valuation workflows or other regulated enterprise domains.

Skills

AWS
Machine Learning
Agile
Azure
Confluence
Google Cloud
Jira
Stakeholder Management

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