Education & Experience
7.5+ years of relevant software engineering experience
Bachelor's or Master's degree in Computer Science, Software Engineering, Distributed Systems, or related field
Experience with SQL datastores (DB2/MySQL) and Unix/Linux platforms
Understanding of database sharding, replication, and distributed database systems
Experience with distributed file systems (HDFS, S3, or similar)
Knowledge of data consistency patterns across distributed datastores
Proven experience with tools development, automation (CI/CD, Auto Deployment, System Availability), logging and monitoring
Experience with distributed tracing (Jaeger, Zipkin, OpenTelemetry)
Working knowledge of streaming platforms like Kafka for real-time data processing
AI-First Engineering Skills
Hands-on experience with LLM integration and serving at scale (OpenAI API, Azure OpenAI, Claude, Llama, etc.)
Proficiency in AI-assisted development tools (GitHub Copilot, Cursor, Cline, or similar)
Experience building intelligent APIs with AI/ML inference endpoints in distributed environments
Understanding of vector databases (Pinecone, Weaviate, ChromaDB) for RAG applications
Knowledge of prompt engineering and AI model fine-tuning
Distributed Systems Design
Experience designing scalable microservices architectures handling millions of transactions
Knowledge of distributed system monitoring and observability (Prometheus, Grafana, ELK stack)
Understanding of container orchestration in distributed environments
Experience with chaos engineering and resilience testing
Proficiency in distributed debugging and troubleshooting techniques
Professional Capabilities
Ability to write clean, coherent code following established coding guidelines
Strong interpersonal and effective communication skills (both written and verbal)
Highly driven, resourceful, and results-oriented
Experience leveraging AI tools to accelerate development velocity and code quality
Ability to design and communicate distributed system architectures effectively