MSCI Services is looking for a Senior AI Engineer to join our AI team. In this role, you will design and develop highly scalable, robust systems that drive our AI initiatives and data operations. Success depends on strong software engineering skills, familiarity with large-scale distributed systems, and expertise in AI technologies. Our ideal candidate has a proven ability to build reliable platforms (rather than standalone applications) and to iterate effectively over multiple release cycles.
Throughout your work, you'll apply best practices in software engineering and system architecture. If you're passionate about delivering high-impact AI solutions in a dynamic environment, this is an exciting opportunity to have a substantial influence on our AI capabilities through your expertise.
Responsibilities:
- Design and implement scalable distributed systems.
- Architect solutions that can handle large volumes of data for real-time and batch processing.
- Design and develop efficient AI pipelines with automation and reliability across the platform.
- Integrate agentic workflows and AI agents into data extraction processes, and enable systems to perform multi-step reasoning and tool usage to improve accuracy and efficiency of data extraction.
- Deploy, monitor, and maintain LLM-based extraction systems in production, ensuring reliability and scalability. Set up appropriate monitoring, logging, and evaluation metrics to track performance, and perform continual tuning and improvements based on human-in-the-loop feedback.
- Conduct applied research and experimentation with the latest generative AI models and techniques to enhance extraction capabilities. Prototype new approaches and iterate quickly to integrate successful methods into the production pipeline.
- Collaborate with cross-functional teams (data engineers, product managers, domain experts) to gather requirements and align AI solutions with business needs.
Qualifications:
- Experience in applied AI or machine learning engineering, with a track record of building and deploying AI solutions (especially in NLP).
- Hands-on experience with using Generative AI models and APIs/frameworks (e.g., OpenAI GPT-4, Google Gemini).
- Ability to build Agentic AI systems where LLMs interact with tools or perform multi-step workflows.
- Proficiency in Python (preferred) and experience deploying machine learning models or pipelines at scale.
- Good understanding of embeddings, LLM models, and experience with retrieval-augmented generation (RAG) workflows to incorporate external knowledge into LLM-based systems.
- Knowledge of LLMOps and cloud services (Azure, GCP, or similar) for deploying and managing AI solutions.
- Experience with containerization, orchestration, and monitoring of ML models in a production cloud environment.
- Excellent collaboration and communication skills, with the ability to work effectively in a team, translate complex technical concepts to non-technical stakeholders, and document work clearly.
