Software Engineer (I)

Qualifications

• Proficiency in code and system health, data structures and algorithms, debugging, programming, test engineering, and code comprehension.
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience with data structures or algorithms.
• 1 year of experience implementing core machine learning concepts.
• Design and implement production-grade multi-agent AI solutions using modern frameworks optimized for enterprise cloud infrastructure.
• Architect and optimize large-scale ETL pipelines leveraging Kubernetes, container orchestration, and cloud-native AI pipelines to process high volumes of imagery data efficiently.
• Design database scaling strategies using enterprise distributed SQL databases to manage and query massive geospatial and aerial imagery datasets.
• Build automated QA and validation pipelines using LLMs and execute rigorous evaluations for prompts and models.
• Establish automated regression tests, tracing, and observability across LLM agent runs and cloud infrastructure to monitor quality, latency, and cost.

Minimum Qualifications

• Master’s degree in Computer Science, a related technical field, or equivalent practical experience.
• Professional experience in software development, including building large-scale, asynchronous data pipelines using Kubernetes, Docker, or similar tools.
• Extensive experience with Python programming and standard software engineering practices.
• Practical experience with enterprise cloud services (AWS, GCP, or Azure) and containerized infrastructure orchestration.
• Proficiency in schema validation (e.g., Pydantic, Protobuf) and large-scale AI evaluations using precision/recall, F1 score, or LLM-as-a-judge methodologies.

Preferred Qualifications

• Experience with generative AI and Large Language Models (LLMs), including advanced prompting techniques, fine-tuning, and evaluation.
• Background in designing and deploying multi-agent systems and modern agentic orchestration frameworks.
• Experience with tool-calling protocols, API integrations, and function-calling schemas.
• Experience with vector databases and vector search integrated with enterprise cloud databases for RAG architectures at scale.
• Strong understanding of distributed systems and performance optimization in high-growth, high-volume data environments.