Job Specifications
We are building an AI Pod focused on leveraging Generative AI and Machine Learning to automate workflows and deliver high-impact business outcomes across multiple technology and business teams (Business Analysis, Product Management, QA, Development).
The initial focus of this role is a client-facing Proof of Concept (POC) to design and deliver an AI-driven recommendation engine for financial advisors. This solution will analyze advisor holdings and matured assets to recommend suitable products and reinvestment opportunities, helping convert capital from matured assets into new investment vehicles.
The AI Engineer will design, build, and deploy LLM-powered agents and ML-driven components that integrate with enterprise platforms such as Confluence, Jira, SharePoint, BI tools, and internal data sources, while adhering to enterprise-grade security and governance standards.
Key Responsibilities
Develop and deploy AI agents in Azure to support automation and digital transformation initiatives.
Integrate AI solutions with enterprise platforms (Confluence, Jira, SharePoint, BI tools).
Collaborate with cross-functional teams (Business Analysts, Project Managers, Developers, QA) to identify pain points and design AI-driven solutions.
Implement best practices for GenAI development, including prompt engineering, model fine-tuning, and secure deployment.
Contribute to the creation of reusable AI components for broader organizational use cases.
Required Skills & Experience
Intermediate-level development experience with strong programming skills in Python, Java, or similar languages.
Hands-on experience with Azure AI services, cloud-based automation, and deploying AI/ML solutions in an enterprise environment.
Experience building recommendation systems, decision-support tools, or data-driven POCs.
Strong understanding of Generative AI concepts, LLMs, conversational agents, and hybrid ML + GenAI approaches.
Experience integrating APIs and building connectors for enterprise tools and data platforms.
Ability to work directly with business stakeholders in a client-facing capacity to define data requirements and solution design.
Strong problem-solving skills and experience working in an agile delivery model.
Preferred Qualifications
Exposure to AI/ML frameworks such as OpenAI, Hugging Face, LangChain, or similar orchestration frameworks.
Experience designing or operating model orchestration layers (e.g., MCP or equivalent) and managing multiple LLMs.
Familiarity with financial services data, advisor platforms, or investment product workflows.
Knowledge of data security, governance, and compliance considerations in enterprise AI deployments.
Experience with BI tools and analytics platforms used for reporting and decision support.
About the Company
Insight Global is an international professional services and staffing company specializing in delivering talent and technical solutions to Fortune 1000 companies across the IT, Non-IT, Healthcare, and Engineering industries. Fueled by staffing and talent experts, Evergreen, our professional services brand, brings technical advisors and culture consultants to help customers tackle their biggest challenges. With over 70 locations across North America, Europe, and Asia, and global staffing capabilities in 50+ countries, our tea...
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