Senior Software Engineer Platform Engineering, Python / ML & AI 

Role Summary: The Senior Software Engineer supports our line of business operations by building, deploying, and maintaining backend solutions, productionizing machine learning models, and enabling RAG-enhanced LLM calls using modern frameworks and technologies in accordance with industry and Rouse software engineering standards. 

Key Responsibilities:

• Design, develop, debug, and deploy scalable and efficient backend and ML pipeline code. 
• Collaborate with Data Science to productionize ML models, focusing on optimization (e.g., making them faster and smaller), enhancing deployability, and building robust testing frameworks. 
• Perform ad hoc analysis and troubleshooting to resolve issues with deployed systems and ML models. 
• Write code as part of a collaborative team, building backend features and machine learning services that play a critical role in our day-to-day operations. 
• Design, implement, and maintain robust MLOPS and AIOps practices and infrastructure. 
• Develop and implement AI Engineering solutions, including prompt engineering, designing Generative AI workflows, using RAG-enabled LLM calls, and implementing evaluation metrics and confidence scores from LLM outputs. 
• Manage, define, and break down tasks in an agile environment. 
• Mentor other team members. 
• Implement with some autonomy & architect solutions in collaboration with engineering leadership. 
• Own the problem and scope solutions that line up with business objectives 
• Provide a rapid response to the needs of the team 

Skills and Experience: 

• Three to five years experience with Python, Django, or similar web frameworks. 
• Deep experience with core ML concepts, algorithms, and libraries (scikit-learn, Tensorflow, etc.) 
• Experience with techniques for model optimization and deployment (e.g., pre and post-processing, model pruning, quantization) to enhance performance and deployability. 
• Familiarity with data preparation, feature engineering, and data pipeline tools. 
• Familiarity with Generative AI concepts, LLMs, and prompt engineering techniques. 
• Experience in building and evaluating RAG-enabled workflows and implementing confidence scoring for AI systems. 
• Familiarity with Google Cloud Platform or other cloud providers for deploying scalable services and ML workload in a production environment 
• Demonstrated ability to troubleshoot, problem solve, test, and develop solutions independently 
• Ownership mindset and capable of self-managing tasks, scope, and priorities 
• Focused on providing our customers with world-class products and services 

Expected Outcomes (first 12 months): 

• Keep up with the daily needs of our operational team(s) 
• Build performant and scalable backend and full-stack solutions to support new and existing products and features 
• Partner with the Data Science (DS) team to productionize, maintain, and optimize the performance of production-grade machine learning models and services. 
• Successfully design and implement Generative AI features and workflows, incorporating prompt engineering and RAG into production systems. 
• Develop and maintain documentation for new and existing business logic in systems. 
• Be active in the Rouse Engineering community, performing code reviews and sharing knowledge.