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About the role
We are hiring a Principal AI Engineer for a large US financial services organization building out its AI transformation function. This person will architect and implement AI and machine learning systems that solve business problems across the enterprise, with a heavy emphasis on generative AI research, experimentation, and agentic systems.
The work spans rigorous data analysis, statistical evaluation, experimental design, and algorithm development across structured and unstructured data. Solutions range from on demand analytics to fully integrated production systems. You will work closely with cross functional teams and keep senior leadership informed on emerging AI trends, risks, and opportunities.
What you will do
AI development and implementation
- Design, develop, and deploy AI and ML systems that address specific business challenges and deliver measurable value
- Research, test, and apply state of the art generative AI models and solutions
- Build agentic AI systems capable of autonomous reasoning, planning, and tool use for complex task completion
- Create evaluation frameworks to assess model performance, detect hallucinations, and ensure output quality
- Create and maintain model documentation with transparent methodologies
- Set enterprise wide technical standards through reference architectures, design reviews, and model lifecycle gates covering data sourcing, bias audits, and drift monitoring
- Contribute to best practices for AI development and deployment
Analytics and insights
- Extract patterns and insights from complex, multi dimensional datasets
- Apply predictive modeling, machine learning, and optimization techniques
- Translate business questions into well defined analytical problems
- Design and execute experiments with statistically valid methodologies
- Develop analytics for financial services use cases while maintaining regulatory compliance
Collaboration and communication
- Lead projects with limited supervision and act as a technical resource across teams
- Drive cross team initiatives ensuring integration, scalability, and compliance
- Communicate complex technical concepts to non technical stakeholders
- Partner with software, cloud, and data engineers to integrate AI into existing systems
- Work with compliance and security teams to meet regulatory requirements
What we are looking for
Experience
- Bachelor's degree in Computer Science, Statistics, Data Science, Mathematics, or a related technical field. Advanced degree preferred but not required
- 6+ years developing and deploying ML or AI solutions in production environments
Technical skills
- Strong Python, with familiarity in JavaScript and SQL
- Deep expertise in generative AI: prompt engineering, fine tuning, RAG, evaluation frameworks, tool integration, and agentic system design
- Cloud platform experience, AWS preferred, specifically Bedrock, SageMaker, and Lex
- ML frameworks: PyTorch, scikit learn, Hugging Face
- Practical knowledge of deep learning, neural networks, and traditional ML algorithms
- Familiarity with model optimization including quantization and distillation
- AI orchestration frameworks such as LangChain, LlamaIndex, and MCPs
- Data visualization and the ability to tell a clear story with complex analysis
Engineering practices
- Git and GitHub, CI/CD pipelines, and DevOps practices
- Docker and Terraform, containerization and infrastructure as code
- Strong grounding in data structures, algorithms, and software design
- Experience designing observability systems for AI applications
Ways of working
- Clear communicator who builds consensus across teams
- Mentors colleagues and shares knowledge
- Strong analytical thinking and independent problem solving
- Comfortable in Agile environments
