Government and Infrastructure - Service Delivery Center - AI Solution Development Manager

EY•San Antonio, TX

7d•$76,200 - $197,900•Hybrid

About The Position

The Service Delivery Center is made up of high-performing, U.S.-based professionals who work closely with EY engagement teams to deliver project-based work and managed services to government clients. The Service Delivery Center is a core component of the Government and Infrastructure practice. We currently have an opportunity for an AI Solution Development Manager to join our growing AI & Data practice. In this role, you will lead the technical delivery of innovative AI-enabled solutions, including proofs of concept, prototypes, reusable accelerators, and production-ready applications. You will remain close to the technology while guiding teams through solution design, development, testing, deployment, and continuous improvement. You will collaborate with EY engagement teams, technical specialists, and client stakeholders to translate defined business and mission needs into working technology. Your primary focus will be successful technical delivery, including solution quality, team execution, and reliable implementation.

Requirements

Must have ability to obtain and maintain a secret level clearance
Must have a bachelor’s degree and a minimum of 6–8+ years of related professional experience
Must be comfortable working in-person in a hybrid environment
Relevant experience leading the technical delivery of software, data, AI, analytics, or automation solutions
Hands-on development experience with Python and modern backend frameworks such as FastAPI, Flask, Django, or similar technologies
Experience with JavaScript or TypeScript and a modern front-end framework such as React, Next.js, Vue, Angular, Svelte, or a similar technology
Experience integrating generative AI models or services into applications through APIs, cloud services, or open-source frameworks
Experience designing or implementing APIs, application services, data integrations, and secure connections to enterprise data sources
Experience developing and deploying solutions within a cloud environment such as Microsoft Azure, Amazon Web Services, or a comparable platform
Working knowledge of SQL, relational or nonrelational databases, data ingestion, data transformation, and data-quality concepts
Experience with software development lifecycle practices, source control, testing, code review, technical documentation, and deployment processes
Experience leading technical workstreams and providing guidance to developers or other technical professionals
Strong communication, facilitation, and presentation skills
Flexibility and ability to work effectively with nationally distributed teams
Ability to prioritize assignments, meet deadlines, track open issues, and communicate risks or blockers
Excellent English-language skills, both written and verbal

Nice To Haves

Experience building retrieval-augmented generation solutions using vector databases, enterprise search services, embeddings, and related technologies
Experience developing intelligent assistants, AI-enabled workflow solutions, or agent-based applications
Experience moving AI proofs of concept into secure and maintainable application environments
Experience with cloud-native application services, containers, CI/CD pipelines, infrastructure automation, or application monitoring
Experience with Microsoft Azure AI services, Azure OpenAI Service, Amazon Bedrock, or comparable AI platforms
Familiarity with open-source language models, model evaluation, inference optimization, or model fine-tuning
Familiarity with responsible AI, model evaluation, privacy, security, accessibility, and human-centered AI development practices
Experience developing solutions for government clients or within environments that require formal security, documentation, and approval processes
Relevant technical, cloud, agile delivery, or project-management certifications

Responsibilities

Lead the design, development, testing, deployment, and improvement of AI-enabled applications, proofs of concept, prototypes, and reusable technical components
Translate business, functional, and technical requirements into feasible solution designs, delivery plans, and clearly defined development tasks
Provide hands-on technical direction for solutions that integrate generative AI models, data sources, application interfaces, APIs, and cloud services
Guide the development of AI-enabled web applications using modern front-end and back-end technologies
Support the design and implementation of retrieval-augmented generation solutions, enterprise search capabilities, intelligent assistants, and workflow automations
Evaluate technical approaches, frameworks, models, and tools based on solution requirements, client environment, security considerations, and delivery constraints
Lead the transition of successful proofs of concept into secure, maintainable, and scalable solutions when required by the engagement
Establish and reinforce development standards related to source control, testing, code review, documentation, security, deployment, and maintainability
Review solution architecture, code, technical deliverables, test results, and supporting documentation to promote quality and consistency
Identify technical risks, dependencies, blockers, and delivery concerns, and work with engagement leadership to develop practical resolution plans
Coordinate technical work across developers, data engineers, AI and machine learning specialists, designers, and other delivery professionals
Provide technical guidance, coaching, and feedback to Staff and Senior professionals while supporting their professional and technical development
Manage assignments, delivery priorities, dependencies, and team capacity across one or more technical workstreams
Participate in client and engagement-team discussions to clarify requirements, explain technical decisions, demonstrate working solutions, and communicate delivery status
Support troubleshooting and resolution of complex defects, integration issues, performance concerns, and implementation challenges
Promote reuse of proven solution patterns, components, development practices, and lessons learned across engagements
Stay current on relevant developments in generative AI, application development, cloud services, data engineering, and responsible AI
Deliver engagement-specific responsibilities in accordance with established scope, quality, schedule, security, and client requirements