Tech Lead, Finance & Supply Chain Engineering

Responsibilities

• Partner with the Software Engineering and Data Engineering managers as a peer technical leader.
• Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives.
• Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership.
• Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership.
• Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement.
• Work across backend, full-stack, data, and big-data systems, making sound boundary decisions and bringing the right domain experts into the design.
• Partner deeply with Engineering, Applications, Product, Finance, Supply Chain, Security, and other stakeholders to translate ambiguous needs into durable technical systems.
• Raise the technical capability of both teams through design reviews, code reviews, mentoring, written guidance, and reusable reference implementations.
• Protect team autonomy by focusing involvement on consequential decisions, clarifying principles and tradeoffs.

Requirements

• Significant professional engineering experience with sustained staff-level or equivalent impact as an individual contributor.
• Ability to reason across a full-stack application—from user experience and client architecture through backend services, integrations, authorization, and durable state.
• Strong data-engineering judgment across analytical modeling, batch or streaming pipelines, orchestration, lineage, quality, scale, and downstream data contracts.
• Personally designed, built, shipped, and operated consequential systems, and can go from architecture to implementation details without relying on positional authority.
• Led important technical decisions and cross-team initiatives through influence, clear reasoning, and trusted partnership.
• Care deeply about correctness, security, data quality, auditability, operational excellence, and measurable outcomes.
• Communicate clearly with engineers, managers, and non-technical partners; lead with context and principles rather than control.

Nice-to-Haves

• Experience building internal products, developer platforms, workflow systems, or analytics platforms used across multiple teams.
• Experience with LLM applications, durable agents, AI evaluations, plugins, MCPs, or measurement of AI-enabled engineering outcomes.
• Experience in Finance, Supply Chain, accounting, procurement, ERP, or another domain where controls, reconciliation, and traceability matter.