Moody's seeks to build scalable and efficient AI-driven systems using cutting-edge machine learning techniques, including large language models (LLMs), natural language processing (NLP), and AI agents to enhance productivity and deliver measurable value.
Requirements
- 3+ years of experience in backend software development with a focus on Node.js, building scalable and production-grade systems required.
- Hands-on experience with AI applications, including LLM implementations, retrieval-augmented generation, prompt optimization, and fine-tuning methodologies.
- Strong knowledge of cloud platforms (e.g., AWS, GCP, Azure), containerization technologies (e.g., Docker, ECS, Kubernetes), and MLOps practices.
- Proficiency in databases (e.g., PostgreSQL, MongoDB) and caching systems (e.g., Redis, Memcached).
- Familiarity with Python for collaborating on machine learning workflows.
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency.
- Proven ability to implement AI-powered solutions to solve business challenges.
Responsibilities
- Design and implement AI-driven backend systems using Node.js, creating APIs and services to support applications such as NLP, search, recommendation systems, and AI agents.
- Build and integrate large language model (LLM) applications and AI agents using techniques such as retrieval-augmented generation, prompt optimization, fine-tuning, and reinforcement learning.
- Develop end-to-end pipelines for data ingestion, feature engineering, model inference (batch and real-time), and integration of AI-driven workflows into production systems.
- Optimize backend systems for latency, scalability, and cost, applying caching, load balancing, and other performance techniques to support high-volume inference workloads.
- Advocate for and implement MLOps best practices, including monitoring, logging, tracing, automated retraining, and model/prompt versioning to ensure robust and reliable AI systems.
- Build reusable platforms or frameworks that streamline the deployment and monitoring of AI agents and machine learning models.
- Lead the implementation of autonomous agents capable of multi-step reasoning, decision-making, and tool use in production environments.
Other
- Bachelor's degree or higher in Computer Science, Software Engineering, or a related field.
- Ability to collaborate across disciplines and mentor junior engineers.
- Align system design with business outcomes.
- Work in an inclusive environment that encourages innovation and ethical AI use.
- Comply with Moody's Policy for Securities Trading and VEVRAA requirements.
