Moody's · HR, India
Skills: Python, C#/.NET, SQL, MongoDB, AWS
Skills and Competencies
1-2 years of software engineering experience designing, coding, testing, and deploying backend services or cloud-native applications. Solid coding proficiency in Python or C, with experience building application programming interfaces and microservices and a working understanding of distributed systems concepts. Hands-on exposure to large language model applications, including retrieval-augmented generation, prompt engineering, or agentic workflows, with a drive to deepen that expertise. Working knowledge of Amazon Web Services, Google Cloud Platform, or Microsoft Azure, including experience deploying applications through automated pipelines. Experience with relational and NoSQL databases, including PostgreSQL, MongoDB, and Redis; familiarity with vector databases, observability tools, and event-driven patterns. Ability to break down well-defined problems, estimate and deliver work reliably, respond constructively to code review feedback, and collaborate effectively with product managers and engineers. Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and improve operational efficiency.
Education
Bachelor’s degree in computer science, Information Systems, Engineering, or a related technical field.
Responsibilities
Designs and supports backend services and AI-powered features for intelligent data products.
Designs, codes, and tests backend services, application programming interfaces, and data or inference pipelines for well-scoped features, with guidance from senior engineers. Delivers assigned tasks and features through deployment, including production monitoring, follow-up support, and resolution of technical issues. Participates in design and code reviews by proposing options, applying engineering standards, and flagging risks or unclear requirements early. Apply machine learning operations practices, including prompt versioning, automated evaluation, deployment pipeline…
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