AI Engineer
Insight Global (United States)
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 AND EXPERIENCE
2-3 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 AND 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
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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 AND EXPERIENCE
2-3 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 AND 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
#J-18808-Ljbffr
Reference: WJ-3875_16061015 · Posted 11 Nov 2026, 08:18 PM