We are seeking an experienced Senior AI Engineer to design and deliver scalable AI-driven solutions that enable advanced analytics, intelligent decision-making, and business process optimization. The ideal candidate will possess strong expertise in AI solution architecture, Python development, advanced SQL, Azure cloud technologies, and AI-powered analytical platforms. Experience in financial services and regulated environments is highly desirable.
Responsibilities
- Design end-to-end AI and analytics solutions that support predictive, generative, and intelligent automation use cases.
- Develop scalable architectures that support model training, inference, feature generation, and analytical workloads.
- Ensure solutions are resilient, extensible, and aligned with enterprise architecture standards.
- Establish traceability and explainability across AI workflows and outputs.
- Drive architecture decisions that support future AI initiatives and scalability requirements.
Python Development for AI
- Develop clean, modular, and maintainable Python applications for AI and analytics solutions.
- Build reusable components and frameworks supporting machine learning and generative AI workloads.
- Implement robust error handling, logging, monitoring, and automated testing practices.
- Integrate AI/ML models into enterprise applications and business workflows.
- Optimize code performance and maintain high engineering standards.
Advanced SQL & Analytical Engineering
- Develop and optimize complex SQL queries using CTEs, window functions, aggregates, and advanced analytical patterns.
- Support large-scale analytical workloads and performance tuning initiatives.
- Design efficient approaches for entity resolution, relationship discovery, and AI-driven analytics.
- Ensure accuracy and consistency in analytical outputs and reporting.
- Design and implement secure, scalable AI solutions on Microsoft Azure.
- Utilize Azure-native services to support AI model deployment, monitoring, and governance.
- Implement robust security controls including RBAC, managed identities, and compliance requirements.
- Ensure proper environment strategy across Development, Test, and Production environments.
- Optimize cloud resource utilization and cost efficiency.
AI Mapping & Relationship Analytics
- Design solutions supporting entity mapping, relationship modeling, network analysis, and knowledge graph use cases.
- Develop reusable AI features that accelerate future AI initiatives.
- Enable pattern discovery through intelligent contextual modeling and analytical frameworks.
- Support integration of internal and external sources to enrich AI-driven insights.
- Build architectures that can be reused across multiple AI and business scenarios.
- Design AI solutions that meet regulatory, compliance, and audit requirements.
- Ensure explainability, traceability, and governance of AI-generated outcomes.
- Work with business stakeholders across risk, operations, compliance, and analytics functions.
- Apply strong quality controls to ensure accuracy and reliability of AI-driven insights.
Required Skills
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, Data Science, or related field.
- 8+ years of software engineering experience with at least 4+ years focused on AI/ML solutions.
- Strong SQL expertise including query optimization and analytical processing.
- Hands-on experience with Microsoft Azure cloud platform and AI services.
- Experience designing and deploying enterprise-scale AI solutions.
- Strong understanding of AI/ML lifecycle, model deployment, monitoring, and governance.
- Experience implementing secure and compliant cloud architectures.
Preferred Skills
- Experience with Generative AI, LLMs, RAG, Knowledge Graphs, and Agentic AI frameworks.
- Experience with Azure OpenAI, Azure AI Foundry, Azure Machine Learning, and Cognitive Services.
- Familiarity with graph analytics, relationship modeling, and entity resolution.
- Financial Services domain experience including Risk, Compliance, Asset Management, Banking, or Capital Markets.
- Exposure to MLOps, CI/CD pipelines, and AI governance frameworks.
Key Skills
- AI Governance & Explainability
- Entity Resolution & Relationship Modeling