AI/ML Tech Lead (Python, NLP & LLM)

Job Title: AI/ML Tech Lead (Python, NLP & LLM)

Location: Hybrid in Raleigh, NC (3 days minimum onsite)

Job Summary:

Responsible for driving end-to-end delivery of data-driven products that apply Python, natural language processing, and large language models to enterprise use cases in a hybrid work model. The role coordinates cross-functional teams, manages complex roadmaps, and ensures that solutions are reliable, ethical, secure, and aligned with business outcomes in a scalable and sustainable manner.

Required Skills:

• Python
• Natural Language Processing
• Large Language Model (LLM)

Responsibilities:

• Strong knowledge of software development methodologies Agile, Waterfall and modern engineering best practices
• Strong programming skills in languages such as Python, Java J2EE, JavaScript, SQL, and modern frameworks
• Experience designing and building scalable systems, including APIs, microservices, and distributed architectures
• Proficiency in CI CD pipeline design, implementation, and maintenance, including automated testing, deployment, and release management
• Experience with Git-based workflows and GitHub-based automation, including GitHub Actions and GitHub agent capabilities
• Experience with AWS cloud services e.g., EC2, S3, Lambda, RDS, EKS & ECS and building cloud-native applications
• Understanding of cloud architecture patterns, including scalability, resiliency, and cost optimization
• Platform engineering experience, including building and maintaining reusable infrastructure, developer platforms, and self-service tooling e.g., Infrastructure as Code using Terraform CloudFormation
• Familiarity with containerization and orchestration technologies e.g., Docker, Kubernetes
• Proficiency in designing and implementing AI-powered systems, including LLM-based applications, agent frameworks, and workflow orchestration
• Experience developing, evaluating, and deploying machine learning models supervised, unsupervised, or deep learning
• Strong understanding of statistical analysis, experimentation, and model evaluation techniques
• Experience with data processing and analysis tools e.g., Pandas, Spark, or equivalent
• Advanced proficiency in data modeling, data manipulation, and optimization techniques
• Strong knowledge of normalized and dimensional data modeling principles
• Solid understanding of multiple data storage systems relational, NoSQL, and data lake architectures
• Familiarity with MLOps practices, including model lifecycle management, monitoring, and observability
• Knowledge of test-driven development and modern testing strategies across both data and application layers
• Strong understanding of prompt engineering, evaluation strategies, and reliability considerations for AI systems
• Strong research and problem solving skills, including evaluating and applying emerging technologies
• Ability to design, document, and implement complex system and data components
• Strong communication skills, with the ability to work effectively across technical and non-technical audiences