About the role
Engineer responsible for operationalizing and deploying agentic AI solutions into secure, scalable production environments in financial services. Collaborates with AI scientists to translate research prototypes, maintain deployment pipelines, optimize performance, ensure compliance, and support industry partners.
ResearchOnsite
Key Responsibilities
- Collaborate with AI Scientists to translate research prototypes into scalable production systems
- Maintain deployment pipelines for agentic AI and LLM-based solutions
- Optimize system performance, latency, reliability, and cost efficiency
- Implement monitoring, logging, evaluation, and alerting mechanisms for deployed AI systems
- Ensure compliance with enterprise-grade security, privacy, and governance standards
- Support testing, validation, and user acceptance processes with industry partners
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, or related field
- Strong hands-on experience in Python and modern ML frameworks (e.g., PyTorch)
- Experience deploying LLM-based or AI systems into production environments
- Experience with MLOps pipelines, model monitoring, and observability tools
- Solid understanding of software engineering best practices (version control, CI/CD, testing, code reviews)
- Familiarity with cloud platforms (e.g., AWS, Azure)