Job Description

The AI Engineer will be supporting a large-scale transformation program. This role sits at the intersection of advanced analytics, AI, and modern data platforms, with a strong focus on Azure-based data ecosystems and AI enablement. The successful candidate will play a key role in designing, building, and implementing AI-enabled data solutions, supporting both internal analytics modernization and enterprise data platform initiatives. This includes contributing to data product development, dashboard transformation, and cloud migration programs. This is an ideal opportunity for someone who thrives in a consulting-led environment working closely with business stakeholders and technical teams to deliver scalable, production-grade AI solutions. Roles/Responsibilities: - Design, develop, and deploy AI/ML solutions aligned to business and data strategies within financial services environments - Build and implement agent-based tools and AI-driven workflows where applicable - Leverage modern AI tooling such as GitHub Copilot or similar to accelerate development and delivery - Contribute to the implementation of Azure-based data platforms, including data pipelines, data products, and data integration frameworks - Support migration initiatives from legacy platforms (e.g., Teradata, Hadoop-type environments) to Azure - Collaborate with data engineering teams to ensure scalable, reliable data architecture - Support the revamp of internal dashboards and reporting frameworks - Transition legacy reporting (e.g., Power BI dashboards) toward more scalable, product-oriented data solutions - Work closely with analytics teams to translate business insights into technical solutions - Partner with business, product, and technical stakeholders to define requirements and deliver solutions - Operate effectively within a Big 4 consulting model, managing multiple workstreams and client expectations - Communicate technical concepts clearly to non-technical stakeholders

Required Skills & Experience

• ~4+ years of experience in AI engineering, data engineering, or advanced analytics roles - Proven experience in financial services or banking environments - Strong experience with the Azure data ecosystem (e.g., Azure Data Factory, Synapse, Databricks, or similar) - Hands-on experience building and deploying data pipelines and data products - Strong programming skills in Python and SQL - Experience with AI/ML model development and deployment - Background in systems engineering or platform-based delivery models - Understanding of end-to-end data architecture and cloud migration patterns - Strong problem-solving and communication skills - Experience with agentic AI tools, LLM integrations, or AI copilots - Familiarity with GitHub Copilot or similar AI-assisted development tools

Nice to Have Skills & Experience

• Exposure to internal data product models versus traditional BI/reporting approaches - Experience modernizing enterprise reporting ecosystems - Knowledge of financial data regulations and governance frameworks - Experience supporting large-scale enterprise data migrations