AI Architect with VertexAI and Google Cloud Platform

Unikon IT, Inc.; Richmond (VA); Remote; USD 124,000 - 207,000; Full time

Job summary

Unikon IT, Inc. seeks an experienced AI Architect to lead an enterprise-grade Vertex AI and Google Cloud Platform solution in Richmond.

You will define the end-to-end architecture, select AI processors, and ensure API-first design across multiple Google services. The role demands deep cloud expertise, strong Java/Spring background, and a track record of handling large data migrations and secure, scalable platforms.

Qualifications

• 15 years in software engineering with 5 years in hands-on lead role.
• Deep Google Cloud Platform experience including at least one large-scale production system.
• Strong Java Spring Boot background able to review and write production code.
• Proven experience with large-volume data or content platforms and complex data migrations.
• Strong relational data modelling and performance tuning PostgreSQL/AlloyDB; working knowledge of MongoDB.
• Event-driven and asynchronous design Pub/Sub API gateway patterns Apigee containerization and Kubernetes GKE.
• Enterprise security and identity experience Okta or equivalent.
• Excellent written and verbal communication; defend design decisions with senior stakeholders.
• Proven experience architecting AI/ML-enabled applications on cloud Vertex AI Document AI or equivalent model/service selection integration patterns and cost-aware design at volume.

Responsibilities

• Define and own the end-to-end solution across GCS, Cloud Run, GKE, Pub/Sub, AlloyDB, Vertex AI, Document AI, Apigee and Storage Transfer.
• Design an API-first platform with contracts, OpenAPI versioning, and integration patterns for consuming systems.
• Plan partitioning, indexing, and search performance for hundreds of millions of metadata rows in AlloyDB.
• Lead migrations: bucket-to-bucket, file movement, and MongoDB to AlloyDB metadata migration with restartable workflows.
• Lead security activities: OIDC, SAML, IAM, service accounts, encryption, and compliance controls.
• Own AI enrichment, select processors/models, define integration patterns and event-driven flows with reprocessing.
• Define AI cost and performance model, batching strategy, tiering by document complexity and SLAs.
• Produce and review artifacts: HLD/LLD, ADRs.
• Provide technical governance, design reviews, code reviews, and mentoring of juniors/senior engineers.

Skills

Java

Spring

VertexAI

Google Cloud Platform

Tools

GKE

PostgreSQL

MongoDB

Pub/Sub

Apigee

OpenAPI

Storage Transfer Service

Job description

Job Title: -- AI Architect with VertexAI and Google Cloud Platform

Location : Richmond, VA (Remote)

Job Type: Contract
Experience: 12 to 15 years exp

Skills

Mandatory Skills : Java, Spring, VertexAI, Google Cloud Platform.

Job Description:

Key responsibilities

• Define and own the solution across GCS Cloud Run GKE PubSub AlloyDB Vertex AI Document AI Apigee and Google Storage Transfer Service
• Design an APIfirst platform with clear contracts OpenAPI versioning and integration patterns for consuming systems Salesforce ERPJDE internal apps
• Solution for scale partitioning and indexing strategy in AlloyDB for hundreds of millions of metadata rows GCS bucketobject layout lifecycle and storageclass policies search performance at volume
• Lead the migration activities buckettobucket file movement and MongoDB AlloyDB metadata migration manifestdriven restartable reconciliationfirst with zero unnecessary data copying
• Lead the security activities Oktabased authNauthZ OIDCSAML token flows for UI vs system clients IAM and serviceaccount boundaries CMEKencryption signed URLs data classification audit trails and compliance requirements
• Own the AI enrichment solutioning selecting the right mix of Document AI processors Vertex AI models and custom extractors per document type and defining integration patterns APIs SDKs eventdriven flows with failure handling and reprocessing
• Define the AI cost and performance model batching strategy model tiering by document complexity and costperdocument targets balanced against extraction accuracy and SLAs
• Produce and review technical artifacts HLDLLD sequence and flow diagrams ADRs
• Provide technical governance design reviews code reviews and mentoring of leadssenior engineers

Required skills experience

• 15 years in software engineering with 5 years in a handson lead role
• Deep Google Cloud Platform experience including at least one largescale production system
• Strong Java Spring Boot background able to review and write production code
• Proven experience with largevolume data or content platforms and complex data migrations
• Strong relational data modelling and performance tuning PostgreSQLAlloyDB working knowledge of MongoDB
• Eventdriven and asynchronous design PubSub API gateway patterns Apigee containerization and Kubernetes GKE
• Enterprise security and identity experience Okta or equivalent
• Excellent written and verbal communication comfortable defending design decisions with senior stakeholders
• Proven experience architecting AIMLenabled applications on cloud Vertex AI Document AI or equivalent modelservice selection integration patterns and costaware design at volume

Nice to have

• Prior work on documentcontent management ECM or recordsmanagement platforms
• Search technology experience fulltext faceted vectorsemantic search with embeddings
• laC Terraform CICD on Google Cloud Platform costoptimization at scale
• Google Professional Cloud Architect certification