Director of Engineering at The Bike Shop

science, and public policy. By translating advances into scalable, actionable solutions, the center empowers governments and institutions to achieve outcomes traditional approaches cannot. Job Summary The Bike Shop is seeking a strategic and entrepreneurial technology leader to shape the direction of its software, data, and AI capabilities. As the senior technical leader, you will set the technical vision, guide system architecture, and establish engineering practices across all Shop-built systems. You will lead a dual mandate: delivering production-quality software products that strengthen the Shop's public technical reputation and serve as essential internal infrastructure, while also building applied AI and machine learning capabilities. In this role, you will build and lead the Shop's engineering function, including defining the team structure, hiring exceptional talent, establishing technical standards, and developing a multi-year technology roadmap. You will also oversee the technology function's financial resources, including budgets, forecasts, and project investments. Working closely with research leadership, you will help shape the Shop's research agenda by identifying what is technically possible and creating the platforms and capabilities needed to support ambitious Center initiatives. This is a high-impact leadership opportunity for someone who thrives with autonomy and enjoys turning emerging ideas into reliable, real-world systems. Your decisions will influence the Shop's work across the organization and play a significant role in defining its external technical reputation. Responsibilities Product and Platform Delivery Owns the Shop's software product portfolio end to end -- definition, architecture, implementation, release, and ongoing operation -- and holds final decision authority over scope, technical approach, and release readiness. Drives concept-to-production delivery of externally released applied tools, including product definition, user experience and information architecture, implementation, launch, and ongoing operation. Owns public release strategy for Shop software, including open-source governance, API design and versioning, packaging, documentation, and support model. Delivers internal platforms, administrative dashboards, and authoring tools that increase research and operational throughput across the Shop. Owns architecture across a portfolio of concurrent products, determining what is delivered as shared platform versus per-product implementation. Determines when prototypes graduate to production and what hardening is required. Makes build, buy, and adopt decisions (within the University's procurement framework) and owns vendor and open-source dependency strategy. Applied AI/ML Development and Technology Evaluation Leads applied AI/ML engineering aligned to Shop priorities, including agentic system design, entity resolution and normalization, anomaly detection, and predictive modeling. Translates Shop research objectives into system requirements, architecture, and delivery plans, and surfaces technical constraints, costs, and opportunities early in direction-setting. Identifies where new engineering capability would enable work not currently possible, and defines the build effort required to open those directions. Prototypes and evaluates emerging AI capabilities and determines which are engineered into production systems. Represents the Shop's technical work externally through technical briefings, product demonstrations, and public software releases. Maintains working knowledge of emerging technologies in scientific and commercial communities and translates them into Shop capability. Technical Direction, Architecture, and Operations Owns end-to-end architecture of the Shop's cloud platform, including service decomposition, data flow, storage, identity and authorization, and deployment topology. Selects the Shop's core technology stack -- languages, frameworks, data stores, cloud services -- and defines migration paths as it evolves. Defines the architecture for the Shop's AI and agentic systems, including orchestration, tool and protocol interfaces, state and memory management, and evaluation harnesses. Owns model selection and integration decisions for Shop systems, operating within University enterprise agreements and institutional AI governance requirements, and evaluating cost, latency, privacy, and reproducibility tradeoffs. Designs evaluation and monitoring approaches for non-deterministic systems, including regression testing and quality measurement of model-based components. Sets reliability and performance targets -- availability, latency, throughput -- and owns the architecture required to meet them. Designs data ingestion and processing pipelines at the scale required by Center systems. Establishes the architecture review process and serves as final technical approver for designs spanning more than one system. People and Resource Management Establishes and staffs the Shop's engineering team, supervising 2-3 professional engineering staff across existing and newly created positions. Recruits, hires, onboards, and develops technical staff; sets performance expectations and conducts annual performance reviews. Manages the financial resources of the Shop's technology function including budgets, finances, and forecasts across all responsibilities and projects; owns cloud infrastructure spend, tooling and licensing, and vendor contracts, including forecasting and cost optimization at scale. Supervises student technical contributors and mentors junior engineers. Serves on the Shop's senior leadership team and advises Shop leadership on technology strategy, investment, risk, and the technical feasibility, cost, and delivery timeline of proposed Shop directions. Contributes to project planning, project reporting, and recruitment. Ensures Shop technical activities comply with institutional, state, and federal policies, including University enterprise agreements governing AI services, institutional AI governance requirements, data security, and the handling of sensitive and restricted data. Manages employees by establishing annual performance goals, allocating resources, assessing annual performance, and determining individual merit, incentive and/or promotional increases. Provides technical oversight and develops standards, guidelines, and processes for application systems. Creates plans to translate business requirements into well-designed applications while balancing user and business needs, technical competencies, industry developments, and time constraints. Advises decisions on project and infrastructure needs, including the evaluation of server technologies, languages, platforms, and frameworks. Develops timelines and project plans for the team. Performs other related work as needed. Minimum Qualifications Education: Minimum requirements include a college or university degree in related field. Work Experience: Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline. Certifications: --- Preferred Qualifications Experience: 7 years of experience leading technical teams or functions. Track record of senior technical leadership at organizations delivering software at scale, including in early-stage or rapidly scaling environments. Experience building an engineering function, including hiring, technical standards, and process definition. 10+ years of engineering leadership, including responsibility for team structure, technical roadmap, and delivery outcomes. Experience delivering software-as-a-service and data-as-a-service products to external users. Experience owning a technology budget, including cloud cost forecasting and optimization. Experience partnering with technical or scientific stakeholders to translate their objectives into delivered production systems. Advanced degree in computer science, engineering, or a quantitative discipline, or equivalent professional experience. Technical Skills or Knowledge: Production experience with large language model and agentic systems, including multi-agent orchestration frameworks, tool and protocol integration standards, self-hosted and API-based inference, evaluation, and prompt engineering. Applied machine learning in production, including entity resolution and normalization, anomaly detection, predictive modeling, and feature engineering. Large-scale data engineering, including high-throughput ingestion, data acquisition and extraction, ETL pipelines, deduplication, change detection, and job queues and schedulers. Distributed and real-time systems, including low-latency architecture, concurrency, load balancing, performance and memory profiling, and algorithmic complexity analysis. Cloud infrastructure, including Amazon Web Services (EC2, S3, RDS, Lambda, DynamoDB, SQS/SNS, IAM), Linux administration, deployment automation, CI/CD, monitoring and alerting, log aggregation, and horizontal scaling. Data stores, including relational schema design and query optimization (PostgreSQL, MySQL), migrations, caching layers (Redis, Memcached), and NoSQL document stores. Full-stack development across server and client platforms, including Python, TypeScript/JavaScript, REST API design, WebSockets, session and authentication handling, and OAuth. Test and quality engineering, including automated regression frameworks, unit and integration testing, and crash reporting and triage. Product and design practice, including rapid prototyping, specification authoring, user experience design, information architecture, and usability testing. Preferred Competencies Excellent verbal and written communication skills. Strong analytical and problem-solving skills. Ability to set technical direction under ambiguity and with minimal guidance. Ability to assess technical feasibility of proposed directions and communicate constraints and tradeoffs to non-engineering stakeholders. Ability to balance rapid prototyping against production reliability. Work both independently and as a team member. Confidentiality related to sensitive University matters. Working Conditions Remote position. Occasional evening or weekend hours. Participates in escalation for production services. Occasional travel for conferences and collaborator/partner site visits. Application Documents Resume (required) Cover Letter (required) The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions. When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application. Job Family Information Technology Role Impact People Manager Scheduled Weekly Hours 37.5 Drug Test Required No Health Screen Required No Motor Vehicle Record Inquiry Required No Pay Rate Type Salary FLSA Status Exempt Pay Range $170,000.00 - $185,000.00 The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting. Benefits Eligible Yes The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook . Posting Statement The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination. Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form. All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position. The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu . Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.