AI/ML Engineer

Robotic Process Automation LLC; Pennsylvania; On-site; USD 140,000 - 190,000; Full time

Job summary

Robotic Technologies Automation seeks a senior AI/ML engineer to design and deploy production-grade ML systems in the cloud. You will build LLM-based applications with RAG, implement secure tool orchestration, and manage model lifecycles using AWS SageMaker, Glue, Bedrock and Lambda.

Collaborating with product owners and stakeholders, you will craft scalable data pipelines, apply MDLC best practices, and advance testing, monitoring, and reproducibility across teams while maintaining high

Qualifications

• Experience designing and deploying production-grade ML systems.
• Building scalable data pipelines and ML workflows.
• Managing model lifecycle in cloud environments.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong AWS ML stack knowledge and related tooling.

Responsibilities

• Implement agentic frameworks (LangGraph, AutoGen) and MCP for orchestration.
• Develop LLM-based applications with RAG and evaluation frameworks.
• Deploy models using SageMaker pipelines, ECS/ECR, Lambda; manage CI/CD and monitoring.
• Collaborate with product and stakeholders to align solutions with objectives.
• Ensure security, reproducibility, and scalability across ML projects.

Skills

AI/ML engineering

Data engineering

MLOps

Production ML systems

Data pipelines

Model lifecycle

Python

Software engineering

Security & authentication

Communication & collaboration

Ambiguity handling

Education

Bachelor's degree in Computer Science/Engineering

Master’s preferred

Tools

AWS SageMaker

AWS Glue

AWS Bedrock

AWS Lambda

Docker

Kubernetes

TensorFlow

PyTorch

Scikit-learn

React UI

GraphDB

Git

CI/CD

Job 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.

Qualifications

• 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 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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.