Senior Enterprise Architect

OnTrac; United States; Remote; USD 156,000 - 195,000; Full time

Benefits offered by this job

Medical/Dental/Vision coverage

Life and disability insurance

401(k) with company match

Flexible vacation

Job summary

OnTrac is seeking a Senior Enterprise Architect to lead the design of an AI-native logistics platform on Google Cloud, working across platform, core, and domain teams.

You will define the target-state architecture, implement agentic AI, and ensure scalable data, API, and DevOps practices, reporting to the CTO.

The role requires 10+ years in software or solution architecture, strong GCP and last-mile logistics experience, and expertise in MCP, multi-agent systems, and API management.

Qualifications

• Bachelor’s degree or equivalent with 10 years in software/solution architecture.
• 7+ years in architecture roles and 2+ years delivering generative AI or LLM solutions.
• 3+ years creating production solutions on Google Cloud Platform (GCP).
• 3+ years in last mile delivery, parcel, or logistics tech.
• Experience with API management platforms (Apigee, MuleSoft, Kong, or Azure API Management).
• Strong experience in data engineering, API design, and DevOps/LLMOps.

Responsibilities

• Define target-state architecture for OnTrac’s AI-native logistics platform on GCP.
• Design and build agentic and multi-agent systems with MCP and A2A.
• Architect MCP server ecosystem exposing core services and data as tools for AI agents.
• Design AI-ready data platforms with batch/real-time pipelines and vector stores.
• Define unified data model and event taxonomy for orders, shipments, and related data.
• Define API and integration architecture with REST, gRPC, and OpenAPI/AsyncAPI contracts.
• Apply patterns for distributed/AI systems and publish reference architectures.
• Build proofs of concept and move designs to production alongside engineers.
• Apply AI to last mile capabilities like routing, ETA, and dispatch; improve operations.
• Lead architecture reviews and mentor engineers across teams.

Skills

Architectural leadership

Hands-on AI delivery

GCP expertise

Logistics domain knowledge

API management

DevOps/LLMOps

Stakeholder collaboration

Education

Bachelor’s degree or equivalent

Tools

Apigee

MuleSoft

Kong

Azure API Management

Job description

OnTrac is hiring a Senior Enterprise Architect!

Are you eager to join a dynamic and expanding company where you can both learn and make a meaningful impact? If you possess a strong sense of empathy, enjoy assisting others, thrive in a fast-paced environment, and excel at problem-solving,

Location

REMOTE: This position may be performed remotely in states where the company is authorized to employ individuals.

Compensation

The expected starting base pay range for this position is $156,000 - $195,000, with full potential base salary range over a successful candidate’s tenure in the position of $156,000 - $234,000. Actual compensation will be determined based on experience, skills, internal equity, and other job-related factors.

This position may also be eligible for bonus, commission, or other incentive compensation in accordance with the terms of the applicable plan of up to a 25% Bonus Target.

Employment Logistics

Reporting to the CTO, this position is a hands-on, highly technical architect responsible for designing and building the AI-native platform, data, and integration architecture that powers OnTrac’s last mile delivery network. Working across platform, core, and domain engineering teams, this position defines the target-state architecture on Google Cloud Platform (GCP) for generative AI, agentic workflows, and real-time data, proves designs through proofs of concept and reference implementations, and partners with engineers to take them into production. The role brings deep expertise in LLM frameworks, Model Context Protocol (MCP), multi-agent systems, data engineering, API management, architecture patterns, and DevOps and LLMOps, and keeps the organization at the forefront of rapidly evolving AI technology.

Unpacking the Benefits

Employees are eligible for a comprehensive benefits package which may include:

• Medical, dental, and vision insurance
• Life and short- and long-term disability coverage
• 401(k) retirement savings plan with company match
• Flex vacation in states other than CA, CO, IL, MA, MT, and NE, with accruals up to 96 hours for first year of employment with tenure-based increases up to 160 hours
• Two (2) floating holidays per year
• Paid sick leave*
• Six (6) paid company holidays
• Two (2) weeks paid pregnancy disability leave, four (4) weeks paid parental bonding leave
• Additional wellness and employee assistance programs

Benefits eligibility and offerings are subject to the terms and conditions of the applicable plans and company policies.

The Must-Haves

This position requires a Bachelor’s degree or equivalent and 10 years of relevant experience in software engineering, data engineering, or solution architecture, including at least 7 years in an architecture role and 2 years of hands-on generative AI or LLM solution delivery.

MUST HAVE 3 years of hands-on experience designing, building, and running production solutions on Google Cloud Platform (GCP).

MUST HAVE 3 years of experience in the last mile delivery, parcel, or logistics industry, supporting technology for delivery operations such as route planning, sortation, scanning, tracking, or driver and dispatch systems.

MUST HAVE experience designing and implementing enterprise API management and integration platforms such as Apigee, MuleSoft, Kong, or Azure API Management.

Success in this role requires:

• Deep, hands-on knowledge of agentic AI, including agent frameworks (such as Google ADK, LangGraph, or CrewAI), multi-agent orchestration, tool and function calling, agent memory, Model Context Protocol (MCP), and agent-to-agent (A2A) protocols.
• Expert knowledge of GCP architecture and its AI and data services, such as Vertex AI, Gemini, Vertex AI Vector Search, BigQuery, Dataflow, Pub/Sub, GKE, Cloud Run, and Apigee.
• Expert knowledge of data engineering for AI, including data modeling, batch and stream processing, ETL/ELT, change data capture (CDC), lakehouse design, feature and vector stores, data quality, and data governance.
• Strong knowledge of API management and integration, including API design standards, gateways, OAuth 2.0 and OIDC, event streaming with Kafka and Pub/Sub, and exposing APIs as tools for AI agents.
• Strong DevOps, MLOps, and LLMOps skills, including Terraform, CI/CD tooling (such as GitHub Actions, Azure DevOps, or Cloud Build), Kubernetes, model and prompt versioning, automated evaluation, and LLM observability tools.
• Understanding of last mile delivery and parcel logistics, including the parcel lifecycle, scan events, network planning, routing, geospatial data, and driver and carrier operations, and where AI creates value in each.
• Ability to work in a fast-paced environment, balance hands-on engineering with architectural leadership, and prioritize multiple initiatives.

Google Cloud Professional certifications, such as Professional Cloud Architect, Professional Machine Learning Engineer, or Professional Data Engineer and experience establishing an AI center of excellence, agent platform, or reference architectures and standards in a product-led technology organization are strongly preferred.

Your Mission in Motion

A summary of key responsibilities for the role is outlined below. Additional duties may be assigned as needed to support business objectives.

• Define and own the target-state architecture for OnTrac’s AI-native logistics platform on GCP, spanning shared platform services, reusable core services, domain applications, and the AI and agent layer that runs across them.
• Design and build agentic and multi-agent systems, including agent orchestration, planning and tool use, memory and state management, human-in-the-loop controls, and agent-to-agent (A2A) communication.
• Architect the MCP server ecosystem that exposes core logistics services (orders, shipments, tracking, locations, routing) and enterprise data as governed, reusable tools for internal and external AI agents.
• Design AI-ready data platforms, including batch and real-time streaming pipelines, lakehouse and warehouse architectures, feature stores, and vector stores, using services such as BigQuery, Dataflow, Pub/Sub, Spanner, AlloyDB, and Vertex AI Vector Search.
• Define a canonical, unified data model and event taxonomy for orders, shipments, scan events, locations, containers, and drivers, published as versioned contracts and as semantic context for LLMs and agents, with data quality, lineage, and governance built in.
• Define the API and integration architecture, including API-first design, REST, gRPC, and asynchronous APIs, OpenAPI and AsyncAPI contracts, API management through Apigee, and event-driven integration over Pub/Sub and Kafka, serving applications and AI agents alike.
• Apply and document architecture patterns for distributed and AI systems, including microservices, domain-driven design, event sourcing, CQRS, and saga, alongside agentic patterns such as ReAct, planner-executor, supervisor and router agents, and advanced RAG, and publish reference architectures for engineering teams.
• Build proofs of concept, prototypes, and reference implementations hands-on to validate new models, agent frameworks, and AI tools, de-risk designs, and move quickly from experiment to production; write production-quality code alongside engineering teams.
• Apply AI to last mile delivery capabilities, including intelligent order intake, address validation and geocoding, route optimization, delivery promise and ETA prediction, exception management, AI-powered control tower operations, driver and dispatch assistance, and conversational customer experiences.
• Lead architecture and design reviews, author architecture decision records (ADRs), contribute to architecture governance and AI technology selection, and mentor engineers across teams.

Paving your way to your success

• You are a hands-on, highly technical architect responsible for designing and building the AI-native platform, data, and integration architecture that powers OnTrac’s last mile delivery network.
• You work across platform, core, and domain engineering teams, defining the target-state architecture on Google Cloud Platform (GCP) for generative AI, agentic workflows, and real-time data, proving designs through proofs of concept and reference implementations, and partner with engineers to take them into production.
• You bring deep expertise in LLM frameworks, Model Context Protocol (MCP), multi-agent systems, data engineering, API management, architecture patterns, and DevOps and LLMOps, and keep the organization at the forefront of rapidly evolving AI technology.

Disclosures

• *Washington state employees are eligible for up to 56 hours of paid sick leave annually.
• The salary range above represents the national range for this position. The salary range may be inclusive of several career levels at OnTrac, and the actual base offered may vary depending on several factors including, but not limited to: geographic location, candidate experience and qualifications, job-related skills and competencies, market alignment, and financial considerations.
• Compensation decisions are made based on the specific circumstances of each hire to ensure fair and competitive pay.
• This job posting is anticipated to remain open for at least 30 days from the date of posting.

OnTrac is proud to be an Equal Opportunity Employer

Lasership, Inc. dba OnTrac Final Mile with its affiliates, including OnTrac Logistics, Inc. (collectively, "OnTrac" or the "Company") is an equal opportunity employer. We value diversity and welcome applications from individuals of all backgrounds, abilities, and experiences. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or age. Join us in our commitment to creating a diverse and inclusive workplace.