• Collaborate with a team to understand and implement complex logic in our backend platform solutions. • Write maintainable and scalable code following best practices. • Stay up-to-date with the latest techniques, frameworks, and libraries relevant to Java backend development. • Translate business requirements into technical solutions, estimate time and costs, and determine requirements and specifications. • Develop, test, and deploy backend solutions to our clients' satisfaction. • Provide ongoing maintenance for present and future projects. • Work collaboratively with cross-functional teams to define and develop product roadmaps. • Collaborate with creative and development teams to execute ideas and projects effectively. • Write support documentation and provide training to internal and external users on the solutions provided. • Be willing to work extra hours when necessary, such as during GoLive deadlines or other critical project phases. • Utilize knowledge in iGaming to enhance our solutions and meet industry standards.

• Building n-tier applications using RESTful Services • Collaborating with teams to work on Java/J2EE projects • Utilizing NoSQL and Kafka technologies in software development

Role Description As a part of the AI/Advanced Engineering team, you’ll build and operate backend systems that power SkyFi’s AI/Analytics products—reliable APIs, resilient integrations, scalable data workflows—and you’ll help us responsibly experiment with and integrate LLM-enabled capabilities and RAG pipelines where they add real value to both our customers and internal teams. This is a “strong engineering fundamentals first” role within a team that is spearheading innovation with AI-enabled product features. What You’ll Do - Design, deliver, and maintain backend services that integrate multiple Earth Observation providers and expose stable, well-documented APIs. - Build highly reliable systems: maximize uptime, fault tolerance, observability, and predictable performance. - Own data-intensive workflows (large datasets, geospatial/temporal data) with strong attention to correctness and cost. - Collaborate with product, design, and operations to translate requirements into robust solutions. - Partner with engineers to architect and scale systems with operational excellence in mind. - Contribute to LLM experimentation and integration (evaluation, prompting/tooling patterns, RAG prototypes) in a pragmatic, measurable way. - Help plan and implement MLOps foundations for LLM-enabled services: versioning (prompts/models/data), automated evaluation, deployment workflows, monitoring/alerting, and rollback strategies. - Build the operational tooling that makes AI features dependable in production: observability, cost/performance tracking, quality metrics, and continuous improvement loops. - Design for real-world failure modes (latency, degraded retrieval, hallucinations) with guardrails, fallbacks, and secure-by-default patterns. Qualifications - You thrive in ambiguity and fast iteration: you proactively create clarity through lightweight experiments, prototypes, and tight feedback loops. - You’re a curious, self-directed builder who turns learning into shipped, innovative features. - You have 5+ years of experience delivering production backend systems and you care deeply about reliability, observability, and operational excellence. - You’re highly proficient in Python and comfortable learning/evaluating new tools and technologies quickly. - You have strong experience with Postgres (and relational data modeling), and you’ve built and maintained well-designed REST APIs. - You take end-to-end ownership, communicate clearly, and raise the bar through engineering best practices (testing, code review, CI/CD). - You’re excited to thoughtfully apply LLMs/RAG to create real product value, not as a demo, but as a production capability. - You care about the customer, have strong product instincts, and are relentless in your pursuit of a great product, healthy systems, and clean code. - You have a STEM degree (preferably Computer Science) with solid computer science fundamentals. Nice to Have - Experience integrating LLMs in production (RAG, tool calling, embeddings, eval frameworks, guardrails, prompt engineering). - Geospatial experience (PostGIS, GDAL/rasterio, STAC/COGs, GeoJSON, raster tiling). - Experience with vector search and retrieval systems (e.g., pgvector, Pinecone, Weaviate, Milvus) and workflow orchestration (e.g., Prefect, Dagster, Airflow). - Familiarity with LLM/MLOps tooling (MLflow, W&B, LangSmith, OpenTelemetry/structured tracing). - Cloud experience (GCP a plus) and/or SaaS experience supporting 24/7 services. - Interest in Earth Observation and satellite imagery ecosystems. Benefits - Be well compensated. Possibility for equity. - Receive best-in-class benefits, including premium medical, dental, and vision coverage and 20 days paid time off. - Play a critical role in building a market-changing product in the exciting realm of Space. - Thrive in a fast-paced, dynamic environment that rewards initiative, innovation, and getting things done. Company Description SkyFi simplifies obtaining high-resolution Earth observation data and analytics, ensuring businesses and professionals a seamless and efficient user experience. We're empowering everyone, from individuals to companies, to understand and utilize the power of space for good.

• Design and develop high-performance web APIs using Rust • Work with RESTful architectures to build scalable solutions • Create reliable and fault-tolerant systems • Utilize relational databases for effective data management