Senior Python Engineer

Slingshot Aerospace•Washington, DC

1d•$150,000 - $220,000•Onsite

About The Position

At Slingshot Aerospace, we're on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We're a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software. We move fast, we're not afraid to fail, and we believe the best ideas can come from anywhere—whether you're in engineering, sales, product, or operations. If you want to work on something that truly matters, with people who care deeply about the impact we're making and help shape the future of an industry that's just getting started, you're in the right place. Seeking a Senior Python Engineer to design and deliver secure, scalable, high performance data processing and intelligent application platforms. This on site role (Washington DC–Baltimore area) requires deep expertise in Python, FastAPI, distributed event-driven systems, MongoDB, and in memory datastores such as Redis. The engineer will contribute to system design, build production-ready services and pipelines, and apply best practices across ingestion, transformation, streaming, AI integration, and secure delivery workflows. Experience with RAG systems and Agentic AI workflows is strongly preferred.

Requirements

Expert-level Python experience across ETL, microservices, and distributed data processing.
Strong FastAPI development and optimization experience.
Production experience with Kafka and/or RabbitMQ.
Strong MongoDB expertise: schema design, indexing, aggregation, sharding/replication.
Experience with in-memory databases such as Redis.
Hands-on experience implementing vector search or RAG-based retrieval pipelines.
Experience with agent-driven AI architectures and LLM-powered automation workflows.
Strong Linux proficiency and experience with Docker/Kubernetes.
Demonstrated ability to debug complex distributed or high-scale systems.
Hands-on AWS experience across compute, networking, and data services.
Proven application of Secure SDLC and secure engineering patterns.
Bachelor’s or advanced degree in CS, Engineering, or related field.

Nice To Haves

Experience with RAG systems and Agentic AI workflows is strongly preferred.

Responsibilities

Develop Python-based ETL frameworks, orchestration layers, and high-throughput data pipelines.
Implement and optimize real-time, event-driven streaming architectures using Kafka and/or RabbitMQ.
Build and scale FastAPI microservices with strong focus on performance, resilience, security, and observability.
Design MongoDB schemas, indexing strategies, and aggregation pipelines with attention to performance.
Implement caching layers, session management, and high-speed data access using Redis or similar in-memory stores.
Contribute to the design and implementation of RAG pipelines, vector search integrations, and retrieval optimization.
Implement Agentic AI workflows using LangChain and Crew AI.
Apply Secure SDLC practices across coding, code review, CI/CD, and deployment.
Participate in architecture reviews and contribute to engineering standards for distributed systems.
Troubleshoot complex data, system, and performance issues in production environments.
Support containerization, Kubernetes-native deployment patterns, and AWS cloud integrations.