Computer Scientist II

You are a highly skilled Computer Scientist II responsible for designing and building scalable, distributed systems for next-generation platforms and AI-driven applications. Your expertise in backend engineering, cloud-native architectures, and modern Generative AI technologies will be key in this role. Your key responsibilities will include: - Designing, developing, and optimizing large-scale distributed systems with high availability, scalability, and reliability - Architecting and building backend services and microservices-based applications using modern engineering practices - Developing and maintaining cloud-native applications on AWS, Azure, or GCP - Working with Kubernetes and containerized environments for deployment, orchestration, and scaling - Contributing to the design and implementation of Generative AI solutions, including LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, and Conversational AI platforms - Collaborating with cross-functional teams to deliver high-impact solutions - Driving technical design discussions, architecture reviews, and engineering best practices - Optimizing system performance, observability, reliability, and operational efficiency - Mentoring junior engineers and contributing to a strong engineering culture Qualifications required for this role include: - Bachelors or Masters degree in Computer Science or a related field - 7-9 years of experience in software engineering with a strong focus on backend and distributed systems - Strong programming expertise in Java, Python, or similar backend technologies - Proven experience designing and building distributed systems, scalable backend platforms, and microservices architectures - Hands-on experience with cloud platforms (AWS / Azure / GCP) and Kubernetes & container orchestration - Experience working with Generative AI technologies such as Large Language Models (LLMs), RAG architectures, and Conversational AI systems - Strong understanding of system design principles, APIs and asynchronous systems, scalability, performance, and reliability engineering - Excellent analytical, problem-solving, and collaboration skills You are a highly skilled Computer Scientist II responsible for designing and building scalable, distributed systems for next-generation platforms and AI-driven applications. Your expertise in backend engineering, cloud-native architectures, and modern Generative AI technologies will be key in this role. Your key responsibilities will include: - Designing, developing, and optimizing large-scale distributed systems with high availability, scalability, and reliability - Architecting and building backend services and microservices-based applications using modern engineering practices - Developing and maintaining cloud-native applications on AWS, Azure, or GCP - Working with Kubernetes and containerized environments for deployment, orchestration, and scaling - Contributing to the design and implementation of Generative AI solutions, including LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, and Conversational AI platforms - Collaborating with cross-functional teams to deliver high-impact solutions - Driving technical design discussions, architecture reviews, and engineering best practices - Optimizing system performance, observability, reliability, and operational efficiency - Mentoring junior engineers and contributing to a strong engineering culture Qualifications required for this role include: - Bachelors or Masters degree in Computer Science or a related field - 7-9 years of experience in software engineering with a strong focus on backend and distributed systems - Strong programming expertise in Java, Python, or similar backend technologies - Proven experience designing and building distributed systems, scalable backend platforms, and microservices architectures - Hands-on experience with cloud platforms (AWS / Azure / GCP) and Kubernetes & container orchestration - Experience working with Generative AI technologies such as Large Language Models (LLMs), RAG architectures, and Conversational AI systems - Strong understanding of system design principles, APIs and asynchronous systems, scalability, performance, and reliability engineering - Excellent analytical, problem-solving, and collaboration skills