Senior Manager AI/ML Engineering (Flex)

United Parcel Service Sweden Aktiebolag; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

United Parcel Service Sweden Aktiebolag seeks a Senior Manager AI/ML Engineering to lead the design, development, and production delivery of enterprise AI applications incorporating Generative AI, agentic AI, and cloud-native technologies. This role supports AI-powered enterprise platforms across finance and HR.

The ideal candidate will guide a team across LangGraph, LangChain, GCP, RAG, and knowledge graphs, defining scalable architectures and ensuring reliable, cost-efficient solutions with

Qualifications

• Bachelor's degree in computer science, engineering, or a related field.
• 12+ years of designing and delivering enterprise applications with AI/ML in production.
• Hands-on experience leading AI/ML or LLM-based solutions and engineering teams.

Responsibilities

• Lead end-to-end AI/ML engineering across frontend, backend, AI/agent layers, orchestration, data, and cloud services.
• Define scalable architecture patterns supporting multiple business capabilities and workflows.
• Balance deterministic workflows, APIs, rules, AI agents, and hybrid approaches for reliability and cost.
• Architect stateful workflows with session management, retries, and recovery patterns.
• Design and build agentic solutions using LangGraph, LangChain, and RAG.
• Deliver domain AI agents for payroll, benefits, labor contracts, and financial planning.

Skills

AI/ML engineering

Team leadership

Cloud-native architectures

LangGraph

LangChain

GCP

RAG

Knowledge graphs

Observability frameworks

Security

Education

Bachelor's degree in computer science or engineering

Tools

LangGraph

LangChain

GCP

Stardog

Vertex AI

GKE

Job description

Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow-people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Description:

This position is hybrid and will require candidates to work in the following UPS IT locations: New Jersey, Atlanta, Maryland, and Kentucky office 3 days a week.

We are seeking a highly skilled Senior Manager AI/ML Engineering to lead the design, development, and production delivery of enterprise AI applications incorporating Generative AI, agentic AI, cloud-native technologies, and enterprise systems. This role supports an enterprise business intelligence platform that delivers domain AI agents across finance and HR areas such as payroll, benefits, labor contracts, and financial planning, coordinated through cross-domain orchestration and an ontology-driven knowledge graph. The ideal candidate combines strong engineering and architecture fundamentals with hands-on experience building AI-powered solutions using technologies such as LangGraph, LangChain, GCP, RAG, MCP, knowledge graphs, and modern observability frameworks. This role requires the ability to determine where AI adds value and where deterministic workflows, APIs, rules, and traditional application patterns provide the better solution.

Key Responsibilities

• Lead end-to-end AI/ML engineering across frontend, backend, AI/agent layers, orchestration, integrations, data, and cloud services, and mentor a team of AI/ML and software engineers.
• Define scalable, reusable architecture patterns supporting multiple business capabilities, personas, and workflows.
• Determine appropriate use of 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 and build agentic solutions using LangGraph, LangChain, RAG, APIs, MCP, and other orchestration patterns, including semantic routing, coordinator/supervisor agents, and cross-domain multi-agent orchestration.
• Deliver domain AI agents for business areas such as payroll, benefits, labor contracts, financial planning, and competitive positioning, including cross-domain questions, scenario modeling, and financial analysis that reduce reliance on spreadsheets and manual reporting.
• 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, including ontology design and federated knowledge graphs (e.g., Stardog) that ground agent responses in governed enterprise data.
• Define non-functional requirements for scalability, availability, performance, resiliency, security, maintainability, recoverability, and cost efficiency.
• Design cloud-native architectures on Google Cloud Platform (GCP) using services such as Vertex AI, GKE, Cloud Run, AlloyDB, BigQuery, Pub/Sub, and Eventarc.
• Establish patterns for AI observability, distributed tracing, LLM evaluation, accuracy benchmarking, monitoring, Responsible AI, and operational readiness, including test-question sets, UAT support, defect triage, and production release gates.
• Define reference architectures, engineering standards, architecture decision records (ADRs), and reusable patterns, and lead engineering teams through hands-on implementation and code reviews.
• Evaluate architecture alternatives through prototypes and proof-of-concepts and clearly communicate technical trade-offs to engineering, product, security, platform, and business stakeholders.
• Guide CI/CD, Infrastructure as Code, containerization, DevSecOps, and production deployment patterns.

Required Qualifications

• Bachelor's degree in computer science, Engineering, or a related technical field.
• 12+ years of experience designing and delivering enterprise applications, including significant hands-on experience building and deploying AI/ML or LLM-based solutions in production and leading engineering teams.
• Strong experience with distributed systems, APIs, microservices, event-driven architecture, data persistence,