Sr. Software Engineer II - Tech Lead - Data Products

Zoro•Chicago, IL

8h•$115,600 - $192,600•Hybrid

About The Position

This is the senior technical role on a data product team, in a data organization that is becoming a software-engineering organization and deliberately reinventing how engineering work is performed with AI. You will set the technical direction for what the team builds: APIs, backend services, shared libraries, operational data stores, and data-processing systems; and you will build alongside the engineers doing it. This is an individual contributor role with no direct reports. Every data product team at Zoro runs on a three-way partnership: the product manager owns what gets built and in what order, the engineering manager owns the engineering practice and how engineers grow, and you own how it gets built, including the architecture, the interfaces, the sequencing of the work, and the call on whether a design is ready. You will be measured by what the team ships, not solely by what you ship yourself. The best tech leads spend their time on the decisions that are expensive to reverse and leave the rest to the engineers who will learn from making them. The role sits at the seam between software engineering and data science and asks for real strength in both: you may not be building models yourself, but you need to be credible with the people who do, and able to reason about whether an offline metric will hold up online, what a latency budget means for an inference path, and when a model is the right tool and when a rule would do. We expect Tech Leads to use AI in their own engineering and to shape how their teams use it.

Requirements

Experience as the Tech Lead on a team building production backend services, APIs, internal platforms, or distributed applications.
Experience designing APIs, data contracts, and operational databases that other teams consumed.
Familiarity with asynchronous processing, queues, event-driven systems, and change-data capture, including idempotency, retries, concurrency, and backward compatibility.
Working knowledge of machine learning and data science concepts: feature engineering, evaluation, training and serving skew, drift, and retraining; enough to review a model design and ask the questions that matter, and experience taking a model from notebook to production.
Experience making a team faster, through interfaces, tooling, or decomposition of work.
Comfort leading engineers who do not report to them, and partnering with a product manager whose priorities they do not set.
Familiarity with cloud infrastructure, containers, CI/CD, infrastructure as code, and observability.
Practical opinions about where AI tools are useful, where they are unreliable, and how to improve their output.
Bachelor's or Master's degree in Computer Science, Applied Mathematics, Engineering, or a related field, or equivalent practical experience.
Minimum 7 years building production software, including at least 2 years as the Tech Lead for a team or a significant system.
Experience building, shipping, and operating production software, with strong programming skills beyond SQL.
Hands on keyboard every week, designing, building, and reviewing, not only directing.
Experience leading the design of a system that multiple engineers built on, and owning it through deployment, incident response, and on-call.
Strong grounding in both software engineering and machine learning or data science, and the ability to lead a technical discussion in either.
A record of raising the team's output, delegating the decisions engineers will learn from, keeping the ones that are expensive to reverse, and deciding plainly when a design is ready.
Influence without authority, earning alignment across teams, negotiating interfaces rather than escalating, and explaining a technical decision clearly to engineers, product managers, and leaders.

Responsibilities

Own the technical direction and architecture of your team's systems, break large problems into work the team can execute, and make the calls that are expensive to reverse.
Stay in the code every week, and use AI throughout design, planning, implementation, testing, and review.
Partner with your product manager on feasibility, sequencing, and tradeoffs, early enough to change the plan.
Partner with the Data Scientists and ML Engineers on your team, from problem framing through production serving, monitoring, and retraining.
Design interfaces, service boundaries, schemas, and data contracts that other teams can rely on, and negotiate them with those teams.
Lead design reviews and RFC discussions, and own the call on when a design is ready and on cross-cutting technical tradeoffs.
Grow the engineers around you through how you review, and partner with your engineering manager on where each one needs stretch or support.
Own your team's operational health: on-call quality, observability, and the systems you have in production.

Benefits

Medical, dental, vision, and life insurance plans with coverage starting on day one of employment
Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.
Adoption assistance program
6 free sessions each year with a licensed therapist and Wellhub portal membership to support your mental and emotional wellbeing
At least 18 paid time off days annually for full-time employees
6 company holidays per year
6% company contribution to a 401K Retirement Savings Plan each pay period, no employee contribution required
Tuition reimbursement
Student loan refinancing
Access to financial counseling, education, and tools
Charitable Gift Program - match gift to an eligible educational, cultural, community health, and human service organizations
Employee discounts and admission to various civic and cultural institutions around Chicago
Coffee bar, beer on tap, unlimited snacks, access to the onsite gym, and incredible city skyline views