Lead Backend Engineer (Modeling & Simulation)

About the role

We are seeking a Lead Backend Engineer to join our team. This role involves designing, building, and leading the development of core backend services that power our platform. Key responsibilities include:

• Designing, building, and maintaining backend services, APIs, workers, and integration layers, primarily in Python.
• Leading a small team of backend engineers while staying deeply involved in the codebase.
• Translating product goals, domain requirements, and technical constraints into clear backend designs and implementation plans.
• Partnering with platform engineering leads to ensure services are deployable, observable, secure, and reliable across various environments.
• Partnering with data engineering leads to define service boundaries, data contracts, persistence patterns, and integration points.
• Own backend architecture decisions for service design, API design, domain logic, asynchronous workflows, and system boundaries.
• Building enterprise-grade software that can operate in multiple deployment models, including cloud-hosted, private cloud, customer-managed infrastructure, standalone/on-premises systems, disconnected or constrained environments.
• Establish and reinforce backend engineering standards, including clean service boundaries, typed API contracts, testing expectations, error handling patterns, observability patterns, database migration practices, and secure coding practices.
• Help break down larger initiatives into well-scoped engineering tasks that can be implemented, reviewed, and delivered incrementally.
• Review code, mentor engineers, and raise the quality of backend implementation across the team.
• Debug complex production issues across services, databases, queues, APIs, infrastructure, and integrations.
• Contribute to architecture discussions and make pragmatic tradeoffs between speed, correctness, reliability, and long-term maintainability.

Requirements

• Strong professional experience as a backend software engineer building production enterprise software.
• Strong programming ability in Python.
• Experience designing and implementing backend services, APIs, background workers, and integration layers.
• Experience leading technical work for a small team, including design guidance, code reviews, mentoring, and delivery ownership.
• Strong understanding of service architecture, domain modeling, API contracts, and backend system design.
• Experience with relational databases, especially PostgreSQL or similar systems.
• Strong SQL and data modeling fundamentals.
• Experience working with ORMs and migration frameworks such as SQLAlchemy, Alembic, Django ORM, or comparable tools.
• Experience building systems that run in production with real reliability, security, deployment, and operational constraints.
• Experience with cloud deployment patterns in AWS, Azure, GCP, or similar environments.
• Experience building or supporting software deployed outside of standard SaaS environments, such as on-premises deployments, private infrastructure, customer-managed environments, appliance-style deployments, disconnected or restricted networks.
• Able to reason about system boundaries, failure modes, data consistency, observability, and operational support.
• Strong communication skills and comfort working across backend, platform, data, product, and domain teams.
• Able to convert ambiguous requirements into practical engineering plans and working software.

Preferred

• Experience with FastAPI, Flask, Django, or similar Python backend frameworks.
• Experience with Pydantic, OpenAPI, JSON Schema, protobuf, or other typed contract systems.
• Experience with asynchronous processing, message queues, event-driven systems, or workflow orchestration.
• Experience with containerized services using Docker, Kubernetes, or similar platforms.
• Experience building systems for regulated, security-sensitive, defense, government, financial, healthcare, or other enterprise environments.
• Experience with deployment models that require strong packaging, reproducibility, versioning, and offline installation support.
• Experience with observability tooling such as structured logging, metrics, tracing, health checks, alerting, service dashboards.
• Experience with authentication, authorization, RBAC, audit logging, and secure service-to-service communication.
• Experience designing systems that integrate with external services, legacy systems, third-party APIs, simulators, data pipelines, or customer-owned infrastructure.
• Experience with geospatial systems, simulation systems, planning systems, logistics systems, or other complex operational domains.
• Experience helping teams establish engineering practices without adding unnecessary process or slowing delivery.