Staff Software Engineer

We're looking for a staff engineer to be the design authority for how software products are built across our engineering organization. A senior IC role: your impact is the design standards and decisions every team builds against, not just the code you write. You are also the technical owner, making sure the data pipeline solutions move from the prototyping phase to production. What You'll Own: Design authority: the standards and hard design decisions every team builds against. Data pipeline Productionization: Data Science solutions made production-ready by design. Evolvability: systems that stay correct and changeable as the business and AI domain move. Craft: a measurable lift in the design judgment of the engineers around you.

The core responsibilities for the job include the following:

Design Authority Goal:

• Every team builds against a shared, high design standard.
• Set the design bar to define the standards for OO and functional decomposition, SOLID, and design patterns, as shared practice across teams.
• Arbitrate the hard calls to the final technical authority on contentious trade-offs: service boundaries, domain models, data and API contracts, and messaging.
• Establish reusable patterns, reference architectures, and decision records others adopt, so good design scales without you in the room.

Data Pipeline Productionization Goal:

• AI work reaches production reliably, proven early rather than late. Own the engagement with data science from prototyping and validation so models and LLM solutions are production-ready by design: serving, integration, performance, and scale.
• Guard evolvability to keep today's systems correct, understandable, and changeable as the business and AI domains evolve.

People and Craft Goal:

• The whole org's design judgment rises.
• Raise craft through deep design and code reviews across teams, to teach rather than gate.
• Multiply engineers: grow senior and junior engineers alike; your success is how much better the engineers around you get.

Requirements:

• Expert-level Python: deep, hands-on Python (3. x), you set the bar for Python quality on the team, fluent in scalable, production-grade services.
• Proven systems architecture: extensive hands-on experience architecting and building large-scale distributed production systems end-to-end; built yourself, not just guided or reviewed.
• Experience: 12+ years shipping production software, as the design authority on complex systems, with cross-team influence beyond your own team. AI-native SDLC; AI-driven development practices and standards.
• Design judgment is the heart of the role. Apply and demonstrate day-to-day, and can reason about and defend OO and functional decomposition, turning ambiguous requirements into clean, well-bounded components, and knowing which approach fits. SOLID and design patterns are applied with judgment about when each is warranted, not by default.
• Domain-Driven Design: bounded contexts and domain models that carve workflows into coherent service boundaries. Test-driven design is designing for testability, so quality is built in, not inspected in. Data and interface design data modelling and schema evolution, versioned API contracts, and cross-service coupling trade-offs. Microservices architecture: service decomposition and the contracts that hold a distributed system together. AI/ML design judgment working judgment on when an LLM vs. a purpose-built vs. a simpler model fits, and the architectural trade-offs each imposes on the surrounding system.
• Hands-on in our stack: language and services: modern engineering practice, building and operating microservices, and UML or equivalent. Data and messaging: PostgreSQL and MongoDB; RabbitMQ or equivalent; REST / gRPC API design.
• Cloud-native and delivery: Docker and Kubernetes (AKS or self-hosted); CI/CD; Git workflows; container registries.
• Observability and AI in production: logging, metrics, and tracing as a design concern; serving patterns for ML/LLM workloads.
• Communication: systems thinking and articulating and defending design decisions to engineers, product, and executives. Close equivalents are fine; tools are learnable; design judgment and hands-on productionization are what we're hiring for.
• Preferred experience in regulated or compliance-heavy environments, and with AI governance / responsible-AI practices. Certifications in Kubernetes, Azure, or related areas.
• Bachelor's or master's in computer science, information technology, or a related field, or equivalent hands-on experience.