- 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.
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.
