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Quindar is seeking a Senior Software Engineer to lead the design and development of mission-planning systems that support real-world spacecraft operations. You will focus on optimization, scheduling, operational automation, and high-performance backend services across the platform.
You'll work primarily in Python to build reliable production systems that solve computationally demanding planning problems. These systems must process large search spaces, respond with low latency, and scale from individual spacecraft to large satellite constellations. You will develop and validate algorithms, design distributed services, and improve the performance and operational resilience of mission-critical workflows.
This role sits at the intersection of optimization, backend software engineering, and space operations. You'll collaborate closely with software engineers, flight dynamics engineers, satellite operators, frontend engineers, and product leaders to turn complex operational requirements into maintainable and scalable software.
Key responsibilities include:
- Lead the design and implementation of mission-planning, scheduling, optimization, and operational-automation systems
- Develop and validate algorithms that solve complex planning and resource-allocation problems across large solution spaces
- Build high-performance APIs and distributed services for low-latency and compute-intensive workloads
- Improve the scalability, reliability, observability, and operational readiness of mission-critical systems
- Collaborate across software, program, product, and operations to turn complex requirements into robust production solutions
- Help shape technical direction, mentor other engineers, and use automation and AI-assisted practices to improve engineering velocity and quality
Quindar encourages engineers to seek leverage through automation and AI-assisted development, using modern engineering tools to accelerate implementation, deepen validation, improve debugging, and reduce operational friction while maintaining high standards for correctness and reliability.
REQUIREMENTS:
- Bachelor's degree in Computer Science, Aerospace Engineering, Applied Mathematics, Operations Research, or a related technical field—or equivalent practical experience
- 6+ years of professional software-engineering experience involving backend systems, distributed systems, optimization, planning, modeling and simulation, or related technical domains
- Strong proficiency in Python and deep experience designing, building, and operating production backend systems
- Experience developing high-performance software for low-latency, compute-intensive, or data-intensive workloads
- Applied experience with optimization, scheduling, search, planning, or resource allocation, using techniques such as constraint programming, mixed-integer programming, vehicle routing, heuristics, or other operations-research methods
- Strong knowledge of algorithms, data structures, computational complexity, performance analysis, and system profiling
- Experience designing and troubleshooting APIs, distributed systems, relational databases, and containerized cloud applications
- Strong software-engineering fundamentals, including architecture, testing, CI/CD, observability, and modern Git-based workflows
- Demonstrated experience independently driving complex software from concept and technical design through production deployment and operation
- Active U.S. Secret security clearance, with the ability to maintain it throughout employment
- Must be a U.S. citizen, national, lawful permanent resident, refugee, or asylee—or eligible to obtain required authorizations from the U.S. Department of State (ITAR compliance)
Desirable qualifications:
- Experience with flight dynamics, orbital mechanics, astrodynamics, spacecraft operations, or aerospace modeling and simulation
- Ability to translate ambiguous operational needs into well-defined planning, optimization, and software problems
- Hands-on experience with cislunar mission design, trajectory planning, or operations in the Earth-Moon system
- Experience evaluating algorithmic approaches based on solution quality, runtime, scalability, reliability, and operational constraints
- Ability to balance long-term architectural thinking with pragmatic, iterative delivery and communicate clearly across disciplines
