Sr. AI Engineer

***No C2C, this role is FTE only and is unable to consider sponsorship at this time***

Location: Our client is targeting someone who can do hybrid in Charlotte, NC

About the Company:

Our client is a leading organization in the financial services space, partnering with professionals across the United States to deliver a broad range of financial products and services. The company focuses on expanding access through strong product offerings, innovative marketing, and advanced technology.

About the Team:

The AI & Analytics team is focused on building next-generation intelligent capabilities across the organization. The team combines modern machine learning, data engineering, and automation to enhance operations, improve decision-making, and support business growth. This is a fast-paced, collaborative, and experimentation-driven environment partnering cross-functionally with technology, operations, and business leaders. The team develops AI solutions including predictive models, enterprise automation, retrieval-augmented systems, and generative AI applications while maintaining strong governance, transparency, and responsible AI practices.

Position Overview:

The Senior Machine Learning / AI Engineer will play a key role in designing, building, and deploying scalable AI systems. This individual will develop production-grade machine learning models, generative AI applications, and automated workflows that drive efficiency and business impact.

Key Responsibilities:

• Design, build, and deploy machine learning models and AI systems at scale
• Develop LLM-powered applications including RAG pipelines, agent workflows, and decision support tools
• Partner with cross-functional teams to translate business needs into technical solutions
• Collaborate with data engineering to ensure data quality and availability
• Mentor team members on best practices in MLOps and model development
• Implement monitoring, observability, and governance frameworks
• Maintain standards for security, compliance, and responsible AI usage
• Evaluate new tools, models, and frameworks to enhance capabilities
• Present insights and technical solutions to both technical and non-technical stakeholders

Qualifications:

• Strong proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience building and deploying machine learning models in production environments
• Hands-on experience with large language models, transformers, embeddings, vector databases, and retrieval-augmented generation
• Experience designing end-to-end AI pipelines from data ingestion through deployment and monitoring
• Familiarity with prompt engineering, fine-tuning, and model optimization techniques
• Experience with MLOps tools such as MLflow, Databricks, Weights & Biases, or SageMaker
• Knowledge of agent frameworks such as LangChain, Semantic Kernel, CrewAI, or AutoGen
• Experience with cloud platforms, preferably AWS, as well as containerization and orchestration
• Strong SQL skills and experience working with modern data platforms such as Snowflake, Redshift, or BigQuery
• Experience building APIs, microservices, and distributed systems
• Ability to evaluate model performance and optimize for accuracy, fairness, and reliability
• Strong critical thinking and problem-solving skills
• Ability to translate business requirements into scalable technical solutions
• Strong communication skills with the ability to explain complex concepts clearly
• Experience working cross-functionally with engineering, data, and business teams
• Ability to mentor and influence team members and stakeholders

Preferred Qualifications:

• Experience in financial services, insurance, or other regulated industries
• Exposure to AI governance and responsible AI frameworks
• Experience with data governance or model lineage practices
• Familiarity with experimentation frameworks or A/B testing
• Knowledge of reinforcement learning, recommendation systems, or advanced NLP techniques