Principal Software Engineer - OMNI Technology (REMOTE)

DICK'S Sporting Goods

1d•$150,000 - $180,000•Remote

About The Position

At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! OVERVIEW: At DICK’S Sporting Goods, we take a people-centric approach to everything we do. Our Athletes, how we refer to customers, and our Teammates, how we refer to our employees, are at the center of every decision we make so that we can provide transformational experiences online, in store, and in sport. When you join Technology at DICK’S Sporting Goods, you’re joining a true team that wins together. We help our Athletes and fellow Teammates better their best by innovating solutions to interesting business problems and empowering every Technology Teammate to be an innovator. And, while we work remotely from all over the United States, we provide virtual and in-person events for the team to hangout, from virtual escape rooms to cheering on the Pittsburgh Pirates at beautiful PNC Park. JOB PURPOSE Acts as the OMNI portfolio-level problem solver, focused on applying AI across engineering teams and product lifecycles within the OMNI technology domain. This role spans end-to-end delivery, fulfillment, and OMNI operations, requiring close partnership with teams both inside and outside OMNI. You will help bring these capabilities to life through AI-driven, spec-based engineering while coaching engineers from junior to senior levels on how to apply these practices effectively. The goal is to deliver best-in-class solutions, strengthen business and software analysis, and serve as an advocate for engineering culture by continuously learning, influencing the broader engineering community, and modeling high standards of technical excellence and governance.

Requirements

AI experience in the following ways: Experience with Spec-first development (not prompt-first)
Experience with Multi-agent orchestration (not single LLM calls)
Experience with Knowledge-centric architecture (your “moat” insight)
Experience with LLMOps discipline (not just experimentation)
Experience with the Build Layer (Spec-driven) Spec Kit, Kiro, BMAD, OpenSpec
Experience with the Execution Layer (Agent frameworks) LangGraph, CrewAI, AutoGen, etc
Experience with the Platform Layer (LLMOps) Lifecycle, monitoring, governance
Web development technologies using JSON, HTML, and CSS preprocessors
JavaScript/Typescript and asynchronous call structures
Experience with React.js, Typescript, RxJs, and other web technologies
Experience with API engineering (spring, cotlin etc), event messaging – Kafka, queue messaging (rabbit)
Deep experience with multiple cache and DB technology (postgres, redis, Azure SQL, Cosmos)
Understands how to optimize AI tokens, and compute to optimize spend.
Unit Testing and Test Coverage technologies
Some experience in using NRWL/NX Mono-repo or similar mono-repo architecture
Experience with Docker, Kubernetes, or other Container technologies
Familiarity with git-based source control
Interest in researching and understanding alternative web technologies
Experience using Agile development methodologies
Experience building custom software solutions
Experience of planning and managing resources to deliver predetermined objectives
Experience leading teams of contractors in an onshore/offshore engagement
Experience mentoring and growing the careers of Software Engineers and Engineering Managers.
Track record of elevating Operational and Engineering excellence bar
Bachelor's Degree or Equivalent Level Preferred
Experience enables job holder to deal with the majority of situations and to advise others (6 to 10 years)
Experience of general supervision of more junior colleagues (7 to 12 months)

Responsibilities

Own development of the most complex existing and new software by analyzing and identifying areas for modification and improvement within the assigned product team.
Develop software that is fast, secure, and reliable to meet defined requirements, while applying AI engineering practices to accelerate design, coding, testing, and delivery.
Lead a collaborative solution design process by gathering input across all product portfolios to define a design system that is viable, scalable, and aligned to the brand.
Lead a cross-portfolio, multidisciplinary team that advances the solution through AI-enabled engineering patterns and clear operating models that support consistent execution and adoption.
Provide subject matter expertise and recommendations on complex or innovative technical developments to improve software quality and better meet user, business, performance, and quality needs.
Recommend AI engineering tools, standards, and practices that strengthen solution design, delivery speed, and maintainability.
Own the end-to-end roadmap of portfolio-level capabilities to facilitate software development and ensure work is prioritized in line with business requirements.
Incorporate AI engineering capabilities and operating model evolution into the roadmap to improve scalability, delivery effectiveness, and cross-team alignment.
Develop medium- and long-term work schedules that enable the organization to achieve its business goals, coordinating across multiple teams.
Align capacity, sequencing, and engagement approaches to the operating model so teams can execute portfolio priorities effectively.
Contribute to the management of a portfolio of programs in partnership with senior teammates.
Help define and mature the operating model, governance approach, and cross-team execution practices needed to deliver portfolio outcomes consistently.
Elicit complex functional requirements using a variety of methods such as interviews, document analysis, workshops, and workflow analysis, and express them in terms of target user roles and goals.
Translate business needs into clear technical requirements, including AI-enabled workflows, decision logic, and specification-driven engineering inputs where appropriate.
Lead design of complex database resources and provide physical modeling and design services to tune database solutions for optimum performance across multiple programs/domains.
Drive the design, implementation, and evolution of robust, well-aligned architecture solutions that operate across the cross-product and domain ecosystem.
Ensure architecture decisions support scalable data flows, integration patterns, and platform foundations for AI-enabled solutions where applicable.
Approve database specifications, ensuring all agreed standards and protocols are followed and data integrity is preserved.
Lead the detection and analysis of cybersecurity incidents, including attacks, breaches, and identified vulnerabilities, and remediate security gaps in line with incident management procedures.
Ensure appropriate governance, controls, and risk management practices are applied to AI-enabled solutions and supporting operating models.