Application Architect (AI & Cloud) - Flex

UPS•Dallas, TX

About The Position

UPS is seeking an Application Architect to lead the end-to-end architecture and modernization of enterprise applications incorporating Generative AI, agentic AI, cloud-native technologies, and enterprise systems. The role combines enterprise application architecture with hands-on design of AI-powered solutions using technologies such as LangGraph, LangChain, GCP, RAG, MCP, and modern observability frameworks. The architect determines where AI adds value and where deterministic workflows, APIs, rules, or traditional application patterns are more appropriate. The position owns architecture across frontend, backend, AI and agent layers, orchestration, integrations, data, and cloud services. It defines reusable patterns, secure architectures, enterprise integrations, data and knowledge patterns, non-functional requirements, and cloud-native solutions on Google Cloud Platform. The architect also establishes AI observability and operational-readiness practices, creates reference architectures and engineering standards, evaluates alternatives through prototypes, communicates trade-offs to stakeholders, and guides engineering teams in implementation and deployment.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field.
12+ years of experience designing and delivering enterprise applications, including significant experience in Application or Solution Architecture.
Strong experience with distributed systems, APIs, microservices, event-driven architecture, data persistence, state management, and enterprise integration patterns.
Hands-on experience designing solutions using Generative AI, LLMs, agentic AI, RAG, and tool-calling architectures.
Experience with LangGraph and/or equivalent agent orchestration frameworks, including stateful workflow and multi-agent patterns.
Experience architecting cloud-native solutions on GCP.
Strong experience integrating applications with enterprise APIs, transactional systems, and legacy platforms.
Experience with enterprise security patterns, including identity, authentication, authorization, service identity, secrets management, and least privilege.
Experience with production observability, distributed tracing, resiliency, performance engineering, and operational readiness.
Ability to develop prototypes and reference implementations to validate architectural decisions.
Strong communication and stakeholder-management skills, including the ability to translate complex business requirements into scalable technical solutions.

Nice To Haves

Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, or a related discipline.
Experience with MCP, LangFuse, OpenTelemetry, Vertex AI, Gemini, OpenAI, or Anthropic ecosystems.
Experience with semantic and knowledge technologies such as Stardog, Neo4j, RDF, OWL, or SPARQL.
Experience with vector search, embeddings, semantic retrieval, and enterprise knowledge platforms.
Knowledge of Responsible AI, AI governance, LLMOps, and MLOps.
Experience designing reusable enterprise AI capabilities or supporting large-scale application modernization.
Relevant cloud, AI, security, or architecture certifications.

Responsibilities

Own end-to-end application architecture across frontend, backend, AI and agent layers, orchestration, integrations, data, and cloud services.
Define scalable, reusable architecture patterns for multiple business capabilities, personas, and workflows.
Choose between deterministic workflows, APIs, rules, AI agents, and hybrid approaches based on reliability, performance, explainability, cost, and maintainability.
Architect stateful and long-running workflows, including session and context management, checkpoints, retries, idempotency, human-in-the-loop interactions, and recovery patterns.
Design agentic solutions using LangGraph, LangChain, RAG, APIs, MCP, and other orchestration patterns.
Define secure multi-persona architectures with appropriate authentication, authorization, entitlements, data-access boundaries, and service identities.
Architect integrations with enterprise APIs, transactional and legacy systems, SaaS platforms, and data services using REST APIs, Apigee/API gateways, MCP, messaging, and event-driven patterns.
Define application data, semantic retrieval, vector search, and knowledge architecture patterns using appropriate relational, graph, vector, and search technologies.
Define non-functional requirements for scalability, availability, performance, resiliency, security, maintainability, recoverability, and cost efficiency.
Design cloud-native architectures on GCP using services such as Vertex AI, GKE, Cloud Run, AlloyDB, BigQuery, Pub/Sub, and Eventarc.
Establish patterns for AI observability, distributed tracing, evaluation, monitoring, Responsible AI, and operational readiness.
Define reference architectures, engineering standards, architecture decision records, and reusable patterns; guide engineering teams through implementation.
Evaluate architecture alternatives through prototypes and proof-of-concepts and communicate technical trade-offs to engineering, product, security, platform, and business stakeholders.
Guide CI/CD, Infrastructure as Code, containerization, DevSecOps, and production deployment patterns.

Benefits

Medical/prescription drug coverage
Dental coverage
Vision coverage
Flexible Spending Account
Health Savings Account
Dependent Care Flexible Spending Account
Basic and Supplemental Life Insurance
Accidental Death and Dismemberment coverage
Disability Income Protection Plan
Employee Assistance Program
401(k) retirement program
Vacation
Paid Holidays and Personal time
Paid Sick and Family and Medical Leave time as required by law
Discounted Employee Stock Purchase Program
Potential eligibility for annual short-term and/or long-term incentive compensation programs