Principal Software Engineer, KYC Risk Assessment

What you'll do

• Architect and implement complex, scalable engineering frameworks using modern software design principles.
• Develop secure, high-quality production code for data-intensive applications and mentor other engineers.
• Design and govern agentic AI systems, including multi-agent workflows and human-in-the-loop controls.
• Establish engineering standards for LLM-based applications, including RAG pipelines and vector store integrations.
• Architect agentic AI-enabled engineering workflows to improve delivery speed, code quality, and operational outcomes.
• Serve as a subject matter expert to advise cross-functional teams on data engineering and platform architecture.
• Influence senior stakeholders on technical strategy and the adoption of advanced technical methods.

What we're looking for

• Formal training or certification on software engineering concepts and 7+ years of applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale.
• Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures in regulated environments.
• Expert proficiency in one or more programming languages, particularly Python and/or Java.
• Advanced knowledge of software application development in disciplines such as cloud, AI/ML, or data engineering.
• Experience with large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools, and orchestration frameworks.
• Practical cloud-native experience with AWS, Azure, or GCP and advanced knowledge of relational/NoSQL databases and vector stores.
• Experience with modern data platforms like Databricks or Snowflake (preferred).