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# AI/ML Engineer

- **Company:** Robotics Technologies LLC
- **Location:** Malvern, PA, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Continuous Integration, Data Dictionary, Information Engineering, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Workflow Management Systems, Cloud Platform System, Okta, Pytorch, ReactJS, Large Language Models, Generative AI, AWS Lambda, Git, Containerization, Scikit Learn, Kubernetes, Information Technology, AWS Glue, AWS Data Analytics, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** June 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c88b22a5e9ebd94b

## About the Role

* 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 TensorFlow, PyTorch, and Scikit-learn.
 * Strong understanding and experience in AWS Machine Learning Stack including:
 * AWS SageMaker
 * 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., LangGraph, AutoGen) and Model Context Protocol (MCP) for orchestration.
 * Knowledge of React UI, GraphDB, and GenAI model performance evaluation
 * Experience with CI/CD, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes).
 * Solid grasp of software engineering principles including testing, version control (e.g., 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.

## Description

* Agentic AI & MCP Integration: Implement agentic frameworks (e.g., LangGraph, AutoGen) 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 SageMaker 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.


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