Lead GenAI Architect: Vertex AI, RAG & Vector Pipelines

TechDigital Group; Nashville (TN); On-site; USD 120,000 - 160,000; Full time

Job summary

TechDigital Group is seeking an experienced leader for Generative AI solutions, focusing on innovative development using Google Cloud Platform and Vertex AI. The ideal candidate will guide the design and implementation of sophisticated AI systems, ensuring high standards and collaboration across teams.

An educational background in Computer Science and more than 8 years of software development experience are required. This role promotes a growth mindset and offers the chance to work on cutting-edge technologies in a dynamic environment.

Qualifications

• 8+ years of experience in software development or engineering roles required.
• Demonstrable experience in delivering Generative AI applications to production.

Responsibilities

• Lead the design and development of Generative AI solutions on Google Cloud Platform.
• Collaborate with stakeholders to understand requirements for AI systems.
• Guide team members in work estimation for AI-related projects.

Skills

Production GenAI experience

Vertex AI / Gemini expertise

Hands-on RAG architecture

Vector/embedding pipelines

DevOps tooling

Cloud native solutions

Agile methodology

Education

Bachelor's degree in Computer Science or related field

Tools

GitHub

Azure DevOps

Diagramming tools (e.g., Visio)

Job description

Mandatory Skills

• Production GenAI experience
• Vertex AI / Gemini expertise
• Hands-on RAG architecture
• Vector/embedding pipelines

Job Description
Lead the design, development, and implementation of scalable, enterprise-grade Generative AI solutions on the Google Cloud Platform, with a strong focus on the Vertex AI suite.
Architect and build sophisticated Retrieval-Augmented Generation (RAG) systems to ground large language models in HCA's proprietary and domain-specific data, ensuring response accuracy and relevance
Design and implement efficient data pipelines for preparing, processing, and embedding data for use in Vector Stores like Vertex AI Vector Search
Develop and apply innovative data grounding strategies and design the necessary data structures to connect LLMs with real-world, real-time information sources
Spearhead the exploration and implementation of Agentic AI concepts to create autonomous systems capable of complex reasoning and task execution.
Champion and integrate the Model Context Protocol to standardize communication between LLMs and external tools, enhancing system capabilities and interoperability.
Promote a collaborative team environment and work closely with colleagues to achieve business objectives.
Collaborate with stakeholders (e.g., business stakeholders, product owners, project managers, and end users) to understand functional and non-functional requirements for AI systems.
Lead investigations and solution proposals for complex development and design problems in the AI domain.
Guide team members in the scope of work estimation and forecasting for AI-related projects.
Perform proof-of-concept and proof-of-technology tasks to secure buy-in from cohorts and stakeholders for new AI initiatives.
Collaborate with team members to successfully execute development initiatives using Agile practices and principles.
Perform other duties as assigned
Practice and adhere to the "Code of Conduct” philosophy and "Mission and Value Statement.”
Education & Experience:
Bachelor's degree Computer Science or related field required
8+ years of experience a Software development or engineering roles required
Demonstrable experience in delivering Generative AI applications to production in a customer-facing or enterprise environment required

Knowledge, Skills, Abilities, Behaviors Required:
Growth mindset and a willingness to learn new skills, technologies, and frameworks in the rapidly evolving field of AI
Advanced knowledge and hands-on experience with GCP Vertex AI, including its generative AI models (e.g., Gemini) and Vertex AI Studio
Deep understanding and practical experience in designing and building Retrieval-Augmented Generation (RAG) architectures
Experience with DevOps tooling (e.g., GitHub, Azure DevOps) and CI/CD for machine learning (MLOps)
Experience with diagramming tools (e.g. Visio)
Strong Experience in cloud native, deploying within cloud environments, serverless development and/or container-based solutions
Knowledge of the Model Context Protocol and its application in enabling LLMs to interact with external tools and data preferred
Familiarity with Agentic AI concepts and frameworks (e.g., LangChain) for building autonomous and multi-agent systems preferred
Experience interfacing with or working within CRM, ERP, eCommerce, or EMR/EHR solutions and common integration patterns
Strong Understanding of agile methodology and software development lifecycles preferred
Ability to sit for long periods of time