Senior Machine Learning / GenAI Architect

Senior Machine Learning / GenAI Architect

Location: Pittsburgh, PA

Work Arrangement: Onsite – 5 days per week

Experience: 6+ years overall, including 1–2+ years in GenAI / AI/ML

Employment Type: W2 / Direct Hire

Work Authorization: U.S. Citizens, Green Card holders, and candidates eligible for H-1B transfer

Sponsorship: Not available

About the Role

We are seeking a highly skilled and innovative Senior Machine Learning / GenAI Architect with strong experience across traditional Machine Learning, Generative AI, MLOps, data architecture, and enterprise AI solutions.

The ideal candidate will have hands-on expertise in Python, Azure, Machine Learning, LLMs, Azure OpenAI, GenAI, agentic AI frameworks such as AutoGen and LangGraph, and Model Context Protocol (MCP).

This role will focus on architecting enterprise-scale solutions that integrate traditional predictive models with Generative AI and agentic AI capabilities, while ensuring scalability, security, governance, and operational reliability.

Key Responsibilities

• Architect and develop enterprise AI solutions that integrate traditional predictive ML models with Generative AI and agentic AI capabilities.
• Maintain and enhance existing predictive models while designing the next generation of AI-powered applications.
• Design, develop, and deploy predictive models using techniques such as Random Forest, Linear Regression, classification, anomaly detection, fraud detection, and churn prediction.
• Build robust and scalable pipelines for data preprocessing, model training, validation, deployment, and monitoring.
• Develop AI/ML solutions using Python and relevant machine learning frameworks such as PyTorch.
• Design and implement enterprise-scale Generative AI and LLM solutions using models such as GPT and Azure OpenAI.
• Integrate LLMs with enterprise data, applications, APIs, and business workflows.
• Design and implement RAG, agentic AI, orchestration, tool integration, and governed AI workflows.
• Develop agentic AI solutions using frameworks such as LangGraph, AutoGen, and MCP (Model Context Protocol).
• Design and implement MCP clients and servers to enable secure integration between AI agents, tools, services, and enterprise systems.
• Translate complex business and technical requirements into scalable, secure, and efficient AI architectures.
• Design ML/AI pipelines with CI/CD automation, model training, validation, deployment, and monitoring.
• Work with Jenkins and DevOps practices to automate AI/ML application deployment and delivery.
• Leverage Microsoft Azure services to build and deploy scalable enterprise AI solutions.
• Work with MongoDB and other enterprise data platforms to support AI/ML and GenAI applications.
• Evaluate emerging AI technologies, frameworks, and models and recommend appropriate solutions.
• Ensure AI solutions follow enterprise security, governance, responsible AI, and compliance standards.
• Collaborate with data engineers, software engineers, architects, product owners, and business stakeholders.
• Provide technical leadership and communicate complex AI/ML concepts clearly to technical and non-technical stakeholders.

Required Qualifications

• 6+ years of overall experience in Data Engineering, Machine Learning, AI, or related technology roles.
• 1–2+ years of hands-on experience with Generative AI / AI/ML projects.
• Strong hands-on experience with Python.
• Strong experience with Machine Learning model development, training, validation, deployment, and monitoring.
• Experience building predictive models using techniques such as Random Forest, Linear Regression, classification, anomaly detection, fraud detection, or churn prediction.
• Strong hands-on experience with Microsoft Azure.
• Experience integrating LLMs with enterprise datasets using Azure OpenAI.
• Strong understanding of Generative AI, Large Language Models (LLMs), NLP, and AI application architecture.
• Experience with LangChain and/or Hugging Face.
• Hands-on experience with agentic AI frameworks such as AutoGen and/or LangGraph.
• Understanding or hands-on experience with Model Context Protocol (MCP), including MCP clients and servers.
• Strong understanding of RAG, LLM orchestration, tool calling, and enterprise AI workflows.
• Experience with MLOps, CI/CD, model training, model deployment, and automation.
• Hands-on experience with Jenkins or similar CI/CD tools.
• Strong experience with MongoDB.
• Experience designing scalable data and AI architectures, preferably within the banking/financial services domain.
• Strong understanding of enterprise data architecture and integration patterns.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work independently with minimal supervision and provide technical leadership.

Preferred Qualifications

• Experience working in the banking or financial services domain.
• Experience with GraphQL and enterprise API integration.
• Experience with PyTorch or other modern ML frameworks.
• Experience designing enterprise-grade AI platforms and governed GenAI solutions.
• Experience with cloud-native AI/ML architectures on Azure.
• Understanding of AI security, responsible AI, model governance, and data privacy.

Interested candidates can share their profile at [email protected]