Engineering Lead (Subject Recognition / On Prem)

About this role

About Auror

At Auror, we’re empowering the retail industry to reduce theft and Organised Retail Crime, a $150 Billion problem globally. It’s high volume crime that’s increasingly organised in nature and is putting people, retailers, and communities at risk every day. Our current mission is to reduce violent retail crime by 50% in 5 years.

Founded in New Zealand 13 years ago, we’re working with some of the best and largest retailers in the world across the US, Canada, Australia, New Zealand, and the UK. Auror is connecting people and intelligence to reduce crime. We’re using technology for good.

In partnership with our leading retail partners, we need people with the passion, determination, and innovation required to overcome one of the world's largest problems. If you’re looking to make a difference with and for the people dedicated to stopping crime, for good, then we want you on our team.

We're also embracing the potential of AI to supercharge our impact—whether that's enhancing the way we detect trends, support our customers, or improve internal workflows. As a company, we're committed to responsibly incorporating AI into how we work and what we build, and we encourage all Aurors to be curious about how AI can elevate their work, regardless of role or function.

The Role

As Engineering Lead (Subject Recognition / On Prem), you'll lead one of the engineering teams responsible for one of Auror's most strategically important product areas. You'll provide technical and people leadership across Auror Subject Recognition (ASR), helping shape the technology that enables retailers to detect and respond to crime in real time.

A significant focus of the role will be taking FaceRec Edge from pilot to reliable, multi-site production. That means defining what a "healthy" deployment actually looks like across a fleet of cameras and on-prem servers, in Detection quality as well as uptime, and building the practice that keeps that estate reliable as it grows.

Working at the intersection of AI, distributed systems, and privacy conscious engineering, you'll ensure our platforms meet the highest standards of performance, reliability, and responsible use of technology.

Success in this role means growing a high performing engineering team that ships with confidence and consistency, delivers innovative Risk Detection capabilities, and enables Auror to continue expanding its impact around the world.

What you’ll do:

- Lead Engineering the Subject Recognition On-Prem team

- Lead engineering for Auror's on-prem face recognition platform — the edge devices, detection pipeline and vendor model integration — setting clear technical direction while keeping the team aligned to shared Risk Detection priorities and customer outcomes.

- Run structured sprint rituals, including stand-ups, retrospectives and planning, keeping the team focused on delivering meaningful outcomes.

- Define and Own Estate Health

- Establish a concrete, agreed definition of a healthy deployment — per camera, per server, per site — spanning detection quality as well as availability, owned jointly with Product and Support.

- Make estate health measurable and actionable, so it drives what the team works on rather than sitting on a dashboard.

- Make Model Upgrades an Organisational Capability

- Own the go/no-go on face recognition model generations, grounded in evidence from shadowed production traffic rather than vendor benchmarks.

- Broker operating-point decisions — the false-positive/false-negative trade-off — to an agreed position with Product and Trust & Safety, and hold our vendor to account on calibration and evaluation support.

- Treat accuracy regression as a reliability concern: detection quality inside the observability framework, with drift detection and a rollout/rollback path that doesn't require a site visit.

- Raise the Bar on Operational Excellence

- Strengthen observability, incident response and escalation across edge and cloud, with blameless postmortems that change something.

- Drive a deliberate, measured reduction in toil — shifting the team's time from firefighting to building capability.

- Set clear engineering standards and drive pragmatic quality across systems where accuracy, latency and reliability directly impact customer trust.

- Guide architectural decisions that evolve Risk Detection into scalable, service oriented platforms that support future growth without unnecessary complexity.

- Grow the Team

- Build and grow a high performing engineering team through coaching, mentoring and technical leadership.

- Eliminate single points of failure through pairing, rotation and written documentation, and actively guard the team's sustainability through the pilot-to-production transition.

- Champion Responsible Engineering

- Champion responsible, privacy conscious engineering practices across Risk Detection, ensuring solutions meet regulatory expectations and retailer privacy requirements while enabling continued innovation.

- Lead Agentic Engineering Processes

- Embed governed, agentic AI practices across the team. Champion LLMs and agentic tooling as force multipliers for delivery, code review and testing, establishing repeatable workflows with appropriate guardrails, human oversight and quality gates. Continuously measure impact and share successful practices across Engineering.

This role reports to Jakob Sorensen https://www.linkedin.com/in/lindehammer/, Director of Engineering.

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I've spent 20 years in engineering, starting out in capital markets in Copenhagen before finding my home in SaaS. I began deep in the technical detail, building real-time pricing and financial risk platforms,…