AI/ML Engineer

Job Description

Insight Global is hiring an experienced AI/ML Engineer to support one of its largest financial services clients. This individual will independently engineer and deploy machine learning and agentic AI solutions while partnering with Data Scientists, Data Engineers, Data Analysts, DevSecOps, and other cross-functional teams to build scalable, production-ready systems. The role will focus on architecting semantic knowledge layers, knowledge graphs, and Graph RAG capabilities that enable AI agents and LLMs to reason over complex business data. Day to day, you will develop data ingestion, retrieval, semantic, and memory pipelines, build and optimize AI applications using Python and SQL, and leverage cloud technologies to deliver enterprise-scale solutions. Additionally, you will support ontology management, data governance, CI/CD automation, testing, monitoring, and deployment best practices while collaborating with stakeholders to solve complex business and technical challenges.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• 3–5 years of experience developing and deploying machine learning, deep learning, and Agentic AI solutions in production environments

- Experience with LLMs, multi-agent systems, and Graph RAG

- Strong software engineering background, including system design, microservices, REST APIs, distributed systems, CI/CD, testing, and version control

- Hands-on experience with Python and SQL, along with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn

- Experience building scalable data ingestion, transformation, retrieval, and processing pipelines

- Strong understanding of model deployment, monitoring, validation, explainability, drift detection, and AI governance

- Experience with relational, NoSQL, and graph databases, as well as cloud-based data and AI platforms

Knowledge of statistics, probability, machine learning algorithms, and predictive modeling techniques Experience with knowledge graphs, semantic retrieval, and ontology-driven architectures.