Position: Senior Lead Python / Applied ML Engineer
Location: Alpharetta, GA Hybrid 3 days a week - Locals only
Duration: 12 Months
Must Have: 15+ years Experience
We are looking for a Senior Lead Python / Applied ML Engineer (Hybrid RAG, NLQ) to join a technologically advanced team focused on developing and enhancing Contact Center Insights platforms. To be successful in this role, the individual should understand the
banking contact center technology landscape and provide creative, scalable solutions that integrate existing capabilities with proprietary system builds, leveraging data science and applied ML to drive measurable business outcomes.
• Develop and enhance an AI insights platform using Python, Hybrid RAG (semantic + keyword retrieval), and grounded LLM workflows to extract, categorize, and summarize insights from enterprise text and knowledge sources.
• Apply data science techniques (exploratory analysis, feature engineering, statistical methods, clustering/classification, topic modeling, sentiment analysis, and evaluation metrics) to improve insight quality, relevance, and accuracy; design experiments and
track model/LLM performance over time.
• Build an NLQ (Natural Language Query) interface and robust API integrations to connect the platform with upstream and downstream systems, enabling automated workflows and seamless consumption of AI outputs.
• Create and maintain a dashboard (React + backend APIs) to visualize trends, classifications, and key metrics; deliver scalable, production-ready services with testing, code reviews, CI/CD, and operational support in an agile, cross-functional environment.
Required Skills
• 15+ years in software development
• 3–5 years hands-on AI/ML experience
• Strong Python experience
• Hands-on with Hybrid RAG and Natural Language Query (NLQ)
• Experience delivering production-grade AI solutions
• Hands-on integrations and data ingestion from Genesys Cloud, Salesforce, and internal/external APIs
• Skilled in monitoring, debugging, and optimizing data pipelines/data flows
• Experience with data modeling, performance tuning, and working with structured & semi-structured data (ETL/analysis)
• Exposure to data science and compute environments like Kubernetes
• Experience with Agile and DevOps practices
• Familiar with JIRA
• Experience with Git and CI tools (Jenkins/TeamCity)
• Strong communication and problem-solving skills
Desired skills
Experience in Python, Hybrid RAG, NLQ Interface
Wealth Management and Contact Center experience
Educational Qualification:
Minimum BS degree in Computer Science, Engineering, or a related field.