Job Description :

Role & responsibilities :

Technical ownership :

- Own the solution architecture end to end : the layered platform, its major components, & the interfaces between them.

- Own the data model : relational system of record, time-series telemetry, topology graph as a projection of the source of truth, & streaming event schemas. Define the contracts that hold the platform together.

- Own the platform framework : the internal service template every microservice inherits from, including observability hooks, resilience patterns, contract testing, API versioning, & CI/CD scaffold.

- Own the per-service low-level designs, at a depth that engineering can pick up & implement against without further translation.

- Own security, identity, & operational engineering framework across the platform.

Leadership & delivery :

- Lead the software engineering team : hire, mentor, performance-manage, & grow engineers across Senior, Mid, & Junior levels.

- Own delivery cadence & quality : sprint planning with programme management, release gates, engineering standards, technical debt management.

- Build a strong engineering culture : code review, test automation, continuous improvement.

- Partner cross-functionally with product, programme, adjacent engineering teams, & customer engineering when required.

- Represent engineering with senior leadership : honest reporting, clear escalation, calm decision-making.

- Grow talent : create clear career paths & mentorship for every engineer on your team.

Preferred candidate profile :

Technical depth, must have :

- 12 or more years of hands-on software engineering experience, with at least 3 years in a principal-architect capacity on systems of comparable complexity (multi-service, polyglot persistence, streaming data, real-time graph).

- Strong data modelling skills : You have personally designed relational schemas at the scale of tens of tables for a transactional system, owned schema evolution, & have an opinion on referential integrity, normalisation, partitioning, & indexing.

- Time-series data at scale (TimescaleDB, InfluxDB, Prometheus, ClickHouse, or equivalent). Retention tiering, downsampling, query design.

- Graph databases for topology (Neo4j, JanusGraph, Neptune, or equivalent). Graph projection from a relational source of truth.

- Stream processing at scale (Kafka & Flink, or equivalent) : Topic design, partitioning, ordering guarantees, schema evolution.

- Strong hands-on Python & Java : Comfortable reading & writing both in production. Modern async patterns.

- Cloud-native operation in production : Containers, Kubernetes, AWS or an equivalent major cloud. OpenTelemetry for observability.

- API design, including REST, OpenAPI, & gRPC. Versioning & backward compatibility for consumers you do not control.

- Low-level design skill. You can decompose a service into a build-ready design with sequence diagrams, failure modes, capacity assumptions, & migration strategy.

- Awareness of AI & machine learning in production : model serving, feedback loops, drift monitoring.

Leadership depth, must have :

- 4 or more years leading engineering teams as an Engineering Manager or equivalent. You have hired, developed, & let go.

- Proven track record of shipping large software platforms end to end. Whole systems, not just features.

- Strong cross-functional partnership skills : You can sit in a room with product, programme, & customer engineers & leave with a single aligned view.

- Clear communication in writing & in person, including with senior leadership.

- Calm under pressure : Sprints will slip. You will not solve that with heat.