Lead Engineer

Job Description:

Senior hands-on engineer to own the technical integrity of a core backend platform — holding engineering quality, making build-vs-configuration calls under architectural direction, and anchoring a small specialist team. Accountable for delivery of their scope: built right, secured, on time, and clearly communicated. A hands-on expert engagement: building, not advising or overseeing.

This is core software development and transaction-processing work — building the operational backbone of a live system. It is not an analytics, data-warehousing, or business-intelligence role.

Must-have summary — the hard bar

• A candidate must clear all of these to be a fit:
• 8–12 years hands-on, currently building — recent, personally-built and delivered work they can speak to in depth.
• Event-driven architecture designed and built — event sourcing / CQRS as a design practice, not just message-bus usage.
• Domain-modeling judgment — can tell a genuinely new pattern from a variation of an existing one.
• Multi-tenant / multi-party security — has enforced tenant isolation server-side; understands event integrity and encryption at rest and in transit.
• Delivery leadership — accountability, execution discipline, clear communication (including to non-technical stakeholders), and sound escalation judgment.
• AI-assisted-development fluency and verification — directs and verifies AI-generated code and test suites, catching plausible-but-wrong output rather than rubber-stamping green.
• Test-strategy judgment — defines what a suite must prove and spots the gaps automated generation leaves.
• Strong Python; working relational-database / projection proficiency.
• Serverless-first cloud-native — object storage and serverless compute as primary building blocks; container fluency; local cloud emulation.
• Executes within locked decisions without relitigating; thrives in a direct, fast-moving small team.

Core skills — full detail

• 8–12 years hands-on, with recent work you personally built and delivered.
• Deep event-driven architecture — event sourcing, CQRS, or similar patterns designed and built, not just used.
• Strong domain-modeling judgment — telling a genuinely new pattern from a variation of an existing one.
• Strong specification skill — turning intent into instructions precise enough to build right the first time.
• Secure-by-design across the platform's layers:
• Domain / data isolation — multi-tenant / multi-party isolation enforced server-side and re-authorized per request; paths and UI are never the isolation boundary.
• Event / transport integrity — event authenticity and tamper-evidence (message signing), and encryption in transit across all edges and internal calls.
• Encryption at rest — across the relational store, the event log, and object / lakehouse storage, with customer-managed keys.
• Security verification of AI-generated code — catches injection vectors, leaked secrets, and authorization bypasses in generated output before they land.
• Test strategy and verification judgment — defines what a suite must prove, and reviews generated tests for genuine coverage rather than green-but-hollow passing (edge cases, error paths, and boundaries automated generation tends to skip).
• Owns the test bar and CI gate — defines what must pass before merge, given humans gate generated changes.
• Hands-on with automated testing frameworks — unit / integration testing, service mocking / stubbing, and test-data generation, alongside local cloud emulation.
• Ownership and delivery discipline — accountable for getting work to done, holds a quality bar under time pressure, drives outcomes rather than waiting for direction.
• Clear communicator — surfaces risk early, reports status crisply, explains technical trade-offs to non-technical stakeholders.
• Sound escalation judgment — knows what to own and decide versus what to surface upward.
• Executes within locked architectural decisions without relitigating them; works well in a direct, fast-moving small team.
• Fluent with modern AI-assisted development tooling — directs and verifies AI-generated code with rigor.
• Strong Python proficiency.
• Working proficiency with relational databases and read-model / projection design — enough to hold the data layer if needed.
• Serverless-first cloud-native build — object storage and serverless compute as primary building blocks.
• Container fluency — containerized local development and container-image packaging of compute.
• Local cloud emulation for development and testing.
• Effective working from principles and open problems, not pre-written tickets.

Advantageous

• Configuration-driven platform experience — change absorbed as config, not rebuilds.
• Cloud-native architecture, streaming / event-processing platforms, serverless.
• Federated / keyless CI credentials, secrets management, least-privilege access design.
• Container orchestration — good to know, not required.

Domain exposure in a data-intensive, operationally complex industry.