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Lead Backend Engineer (Modeling & Simulation)
- United States
- United States
À propos
We are looking for a Lead Backend Engineer to help design, build, and lead development of the core backend services that power our platform. This is a hands-on engineering role for someone who wants to write code while also providing technical leadership for a small team of backend engineers. You will help define service architecture, implementation patterns, API contracts, integration boundaries, and delivery standards across backend systems. You will work closely with platform engineering, data engineering, product, and domain experts to understand what needs to be built, break down ambiguous requirements, and turn them into reliable, maintainable backend services. This role requires experience building enterprise software that can run in modern cloud environments as well as standalone, on-premises, air-gapped, or customer-controlled deployments. We are looking for someone who understands how to build systems that are not only functional, but also durable, observable, secure, deployable, and maintainable in real-world production environments. This is not a people-management-only role. The right person will lead by example through design, implementation, code review, debugging, mentorship, and technical decision-making. What You'll Do
Design, build, and maintain backend services, APIs, workers, and integration layers, primarily in Python. Lead a small team of backend engineers while remaining deeply hands-on in the codebase. Translate product goals, domain requirements, and technical constraints into clear backend designs and implementation plans. Partner with platform engineering leads to ensure services are deployable, observable, secure, and reliable across cloud and on-premises environments. Partner 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. Build enterprise-grade software that can operate in multiple deployment models, including: cloud-hosted environments private cloud environments 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 secure coding practices code review quality 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. Required Qualifications
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 tool 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 Ability 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. Ability to convert ambiguous requirements into practical engineering plans and working software. Strongly 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.
Compétences linguistiques
- English
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