AI ML Architect

• As an AI/ML Arch, you will be responsible for designing, developing, and deploying machine learning models and AI applications that solve complex business problems.
• Expert in Designing and developing search and chat applications that utilize Agentic AI.
• Design and develop AI paved paths for the Alight engineering organization.
• Experiment to evaluate application performance, including designing experiments to evaluate the performance of machine learning models, and then analyze and interpret the results to improve model performance.
• Stay up to date with new tools and technologies and evaluating their potential impact on the business.
• Work with stakeholders to develop and tune algorithms to address business needs. You should be able to effectively communicate your ideas in non-technical terms to help educate business partners
• Evaluate, fine‑tune, and deploy LLMs and foundation models; implement RAG, guardrails, and prompt engineering best practices (conversant with Github Copilot).
• Conversant with LLM security practices – Secure model deployment, Input validation, Data verification (guardrails) etc.
• Write production quality Python code for:
  • Feature Engineering
  • Model evaluation
  • Interface services (APIs)
• Conversant with Spring AI – building MCPs, tools, pre-plugin and post-plugin etc.
• Build high performant Ingestion pipelines.
• Expertise across cloud (AWS), data engineering, ML/GenAI and data ingestion techniques
• Work with CI/CD pipelines (Github Actions, Gitlab, Jenkins)
• Mentor engineers on ML best practices (without direct people management)
• Collaborate on a high-performing, agile team with a global presence

What You’ll Need:

• Overall, 8 -10 years of experience into Data Engineering, Ingestion, AI ML / Gen AI related projects.
• Specifically, AI / Gen AI / ML project(s) with 5+ years of experience
• Master’s degree with preferred concentrations in Computer Science, Data Science, Math, Actuarial Science, Engineering, or related field.

• Experience writing in Python or Spark (ScalaSpark or PySpark) and with popular machine learning libraries such as TensorFlow, Keras, PyTorch, and conversant with JAVA (Spring AI)
• Conversant with Spring boot services
• AI/ML architects should have experience with data preparation and data engineering tasks such as data cleaning, feature engineering, and data transformation
• Knowledge of deep learning architectures and techniques, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and reinforcement learning.
• Familiarity with AWS data and data science tools including SageMaker, Glue, Lambdas, etc.
• Experience in Agile and DevOps development process
  • Must be able to clearly communicate complex technical concepts to a non-technical audience