Senior Backend Engineer - AGI (Python)

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. 5+ years of professional experience in software development, with a proven track record of building and deploying production-ready applications. Strong proficiency in Python and its associated ecosystem. Experience with relational databases (e.g., PostgreSQL) and NoSQL databases (e.g., Redis). Solid understanding of software engineering principles, design patterns, and best practices. Experience building and consuming RESTful APIs. Familiarity with containerization (Docker) and orchestration (e.g., Kubernetes). Experience with version control systems (e.g., Git). Excellent problem-solving, analytical, and communication skills. A passion for learning new technologies and a desire to contribute to a dynamic and evolving team. Domain Expertise (You’re likely to be using one or more of these concepts described here for your day-to-day) Proven experience in optimizing database performance, including query optimization, indexing strategies, and schema design. Experience with database profiling tools and techniques. Ability to identify and resolve database bottlenecks. Strong SQL skills, particularly with PostgreSQL (or similar). Experience with database ORMs like SQLAlchemy. Knowledge of database versioning tools like Alembic. Experience with VoIP protocols (SIP, RTP, WebRTC) and their underlying mechanisms. Experience with telephony signaling and media processing. Familiarity with codecs and their impact on call quality. Experience working with cloud telephony platforms (e.g., Twilio, AWS Connect). Understanding of cloud telephony APIs and their capabilities. Knowledge of call routing, IVR systems, and call queuing. Familiarity with audio processing techniques and libraries. Understanding of networking concepts relevant to telephony (e.g., UDP, TCP, NAT). Experience with Azure Cognitive Services - Speech. Experience with WebSockets. Experience building and maintaining internal tools and libraries, particularly in Python Experience with logging frameworks and tools. Understanding of metrics collection and monitoring systems (e.g., Prometheus, Grafana). Familiarity with alerting platforms and incident response workflows. Experience with cloud platforms (e.g., AWS, GCP, Azure). Familiarity with message queues (e.g., Redis, Kafka). Familiarity with performance testing and profiling tools. Experience with uhashring and mmh3 for consistent hashing, or similar consistent hashing libraries. Extensive experience designing and building microservices-based architectures. Deep understanding of microservices principles, patterns, and best practices. Experience applying DDD principles to software design.