AI​/ML Engineer

Overview

Position Name: AI/ML Engineer

Location: Malvern, PA / Charlotte, NC / Dallas, TX

On-site requirement: 3 days on-site required in one of these locations

Position Type: Full-time

• Agentic AI & MCP Integration:
  Implement agentic frameworks (e.g., Lang Graph, Auto Gen) and Model Context Protocol (MCP) for secure tool orchestration.
• Generative AI Development:
  Build LLM-based applications with RAG, structured output, and evaluation frameworks.
• AWS ML Engineering:
  Deploy models using Sage Maker pipelines, ECS/ECR, Lambda; manage CI/CD and monitoring.
• Security & Identity:
  Integrate Okta/JWT token for API and service authentication; enforce token validation and claims.
• Governance:
  Deliver artifacts required by MDLC/MPLC (Model Documents, Data Dictionary, Monitoring Plan).
• Collaboration:
  
  Partner with PO and business stakeholders to align solutions with objectives.
• Design, develop, and optimize complex data pipelines using machine learning engineering best practices to ensure scalability, efficiency, and reliability.
• Develop and implement robust MLOps pipeline to support the deployment, monitoring, and lifecycle management of AI/ML models in production environments.
• Integrate and maintain data and model pipelines, proactively diagnosing data quality issues and documenting assumptions.
• Collaborate closely with data scientists to validate model-ready datasets and ensure thorough, accurate feature documentation.
• Conduct exploratory data analysis and discovery on raw data sources, incorporating business context to support model development.
• Track data lineage and perform root cause analysis during early-stage exploration or issue resolution.
• Partner with internal stakeholders to understand business processes and translate them into scalable analytical solutions.
• Develop and maintain model monitoring scripts, investigate alerts, and coordinate timely resolutions.
• Act as a subject matter expert in machine learning engineering on cross-functional teams, contributing to high-impact initiatives.
• Stay current with advancements in AI/ML and evaluate their applicability to business challenges.

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 6 years of experience across Artificial Intelligence (AI) / Machine Learning (ML) engineering, data engineering, and MLOps implementation, including:
• Designing and deploying production-grade ML systems.
• Building scalable data pipelines and ML workflows.
• Managing model lifecycle in cloud environments.
• Proficient in Python and familiar with ML frameworks such as Tensor Flow, PyTorch, and Scikit-learn.
• Strong understanding and experience in AWS Machine Learning Stack including:
• AWS Sage Maker
• AWS Glue
• AWS Bedrock
• AWS Data Pipelines
• AWS Lambda Functions
• Experience with Generative AI model development builing LLM based applications with RAG.
• Experience implementing agentic frameworks (e.g., Lang Graph, Auto Gen) and Model Context Protocol (MCP) for orchestration.
• Knowledge of React UI, Graph
  
  DB, and GenAI model performance evaluation
• Experience with CI/CD, containerization (Docker), and orchestration tools (Kubernetes).
• Solid grasp of software engineering principles including testing, version control (Git), and security.
• Familiarity with the Machine Learning Development Lifecycle (MDLC) and best practices for reproducibility and scalability.
• Strong communication and collaboration skills, with experience working across technical and business teams.
• Ability to anticipate ambiguity and devise scalable solutions to address it.

Follow us on Linked In –