Engineering Manager at Benepass · LumiJobs

Responsibilities

This is a hands-on EM role. You have a strong technical background, stay close enough to the systems to review designs, spike prototypes, and debug when it matters, and you do not try to be the best IC in the room. You create the environment — clarity, staffing, and culture — so ICs can own architecture and delivery. Managers own team execution. Project leads own project outcomes. Engineers own the quality and impact of their work.
This role is a culture-carrier for how Engineering works. We hire managers who already operate this way — not people we have to convince.
Our Engineering Operating Principles are the job, not a poster:
Own Outcomes. Accountable for results, not activity. Ownership does not end when code is merged, a ticket is closed, or a project is handed off. Managers own team execution. Project leads own project outcomes. Engineers own the quality and impact of their work. The business experiences outcomes, not tickets.
Projects Are How Work Gets Done. Clear goal, owner, deadline, and definition of success. Teams form around projects, execute, and move on. Core Services also carries operational load — production health, incidents, correctness. We plan for that instead of pretending every hour is roadmap.
One Roadmap. Sales, Ops, Product, Security, and Data all have real priorities. A priority only matters if we are willing to choose it over something else. If everything is important, nothing is.
High Trust, High Accountability. People decide and move without asking permission at every step. Mistakes get surfaced quickly, learned from, and fixed. We do not hide problems, shift blame, or wait for someone else to own it. Weak accountability produces process; we would rather trust people.
Move Fast Through Simplicity. Complexity is expensive. Question meetings, approvals, handoffs, and tools. Prefer principles over rules and judgment over bureaucracy. Ambiguity is a tradeoff we accept for speed.
Work in the Open. Share context early. Document decisions. Surface risks while they are cheap to change. Communication is everyone’s job.
Be AI-Native. AI is a force multiplier and part of the craft. We expect you to use it heavily yourself — not as a talking point, and not only as something you encourage the team to try. People own outcomes. AI expands capacity.
Deliver What We Commit To. Deadlines matter. If a timeline becomes unrealistic, we raise it, cut scope, and make the tradeoff explicit. We do not quietly slip. Reliability builds trust.
ROLE LOCATION & TRAVEL

Qualification

Technical ExpertiseLeadership & EmpathyOutcome-DrivenDisciplined CraftAI-NativeExperienceTechnical LeadershipPeople DevelopmentDelivery ExcellenceAI as a personal craftExperience in fintech

Required

Technical Expertise: Deep software engineering experience in Python/Django (or equivalent backend systems) so you can guide architecture, review PRs, and contribute code when it matters. You think in systems, not endpoints.
Leadership & Empathy: Exceptional communicator who builds high trust and high accountability. You create psychological safety, coach engineers toward growth goals, and do not hide problems or wait for someone else to own them.
Outcome-Driven: You own end-to-end results — from sequencing work to production health. The business experiences outcomes, not tickets.
Disciplined Craft: You fight complexity. Clean code, tests, observability, and small building blocks. Principles over rules; judgment over bureaucracy.
AI-Native: You heavily use AI yourself. This is a personal practice, not a talking point. You can show how it has changed your week: how you write and review code, how you debug, how you prepare for 1:1s and design reviews, how you draft and tighten communication. You are not waiting for a platform team to hand you a workflow. You hold AI-assisted work to the same bar as everything else, and you can teach that to a team without turning it into process.
Experience: 5+ years of software engineering, including 2+ years leading teams of ~3–8 engineers (or equivalent scope), ideally in a startup or SaaS environment.
Technical Leadership: Proven ability to lead design reviews, enforce engineering standards, and prototype in Python/Django (or a comparable backend stack). Comfortable on systems where correctness and reliability are not optional.
People Development: Experience mentoring engineers through 1:1s, setting growth goals against a leveling matrix, handling performance issues directly, and hiring.
Delivery Excellence: Track record of shipping on commitments, creating clarity from ambiguity, and running a healthy SDLC without turning process into the product.
AI as a personal craft: You already use AI heavily in your own work — coding, debugging, planning, writing, and operating a team. You can describe your workflow in concrete terms. You have used it to increase your (and a team’s) effectiveness, not as a demo. You review and own the output. Candidates who “support AI adoption” but barely use it themselves are not a fit.
Experience in fintech, payments, card issuing, wallets, or benefits platforms — especially ledgers, authorization/decisioning, or money movement.
Experience owning high-integrity backend systems (financial, eligibility, identity, or large-scale integrations) where small mistakes have real customer or money impact.

Engineering Manager

Responsibilities

Qualification

Required

Benefits

Company

Benepass

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