Senior AI Engineer - Generative AI & Agentic Systems

Pittsburgh Tomorrow; Pittsburgh (Allegheny County); On-site; USD 150,000 - 210,000; Full time

Job summary

Pittsburgh Tomorrow seeks a Senior AI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI and Agentic AI solutions in Pittsburgh. The candidate will own architecture, model governance, and end-to-end delivery, collaborating with stakeholders and engineering teams.

You will guide AI governance, SDLC enablement, and production operations, while leveraging LangChain, LangGraph, and leading AI platforms. Strong leadership and cloud experience required.

Qualifications

• Bachelor's or Master's degree in related field.
• 10+ years of software engineering and architecture experience.
• 3+ years of hands-on Generative AI, LLMs, and Agentic AI frameworks.
• Strong experience with AI platforms (OpenAI, Anthropic, Gemini, Azure OpenAI, AWS Bedrock).
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
• Strong programming in Python, Java, or related languages.
• Experience deploying AI in enterprise production environments.
• Hands-on experience with cloud platforms (AWS, Azure, GCP).
• Knowledge of MLOps/LLMOps practices, model monitoring, and governance frameworks.
• Proven experience leading cross-functional teams.

Responsibilities

• Design, build, and deploy scalable Generative AI and Agentic AI solutions.
• Architect AI-driven applications using LangChain, LangGraph, CrewAI, AutoGen, and similar ecosystems.
• Define end-to-end solution architecture including model selection, prompts, retrieval, orchestration, APIs, and integrations.
• Lead technical discussions translating business requirements into scalable AI solutions.
• Partner with stakeholders to gather and prioritize requirements and present architectural recommendations.
• Establish AI governance, monitoring, and compliance with security and privacy standards.
• Drive AI SDLC improvements, reusable accelerators, and automation tooling.
• Lead production deployment, monitoring, and incident response for AI applications.

Skills

Leadership

Cross-functional collaboration

Stakeholder management

CI/CD practices

MLOps

Governance

Problem solving

Communication

Education

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field

Master's degree in related field

Tools

Python

Java

OpenAI

Anthropic

Gemini

Azure OpenAI

AWS Bedrock

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Pinecone

Weaviate

Chroma

FAISS

Azure AI Search

Google Cloud Platform

Job description

Job Title: Senior AI Engineer - Generative AI & Agentic Systems
Experience: 10+ Years
Location: Pittsburgh, PA Preferred, Dallas, TX or Cleveland, OH
Employment Type: Full-Time

Role Overview

We are seeking an experienced Senior AI Engineer to lead the design, development, and deployment of enterprise-grade Generative AI and Agentic AI solutions. The ideal candidate will have deep expertise in Large Language Models (LLMs), AI orchestration frameworks, production-grade deployments, model governance, and end-to-end software delivery. This role requires close collaboration with business stakeholders, engineering teams, and leadership to deliver secure, scalable, and compliant AI solutions.

Key Responsibilities

AI Architecture & Delivery

• Design, build, and deploy scalable Generative AI and Agentic AI solutions leveraging LLMs and foundation models.
• Architect AI-driven applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and similar agentic ecosystems.
• Define end-to-end solution architecture, including model selection, prompt engineering, retrieval systems, orchestration, APIs, and integrations.
• Lead technical discussions and translate business requirements into scalable AI solutions.

Stakeholder & Client Engagement

• Partner with internal stakeholders and business leaders to gather, refine, and prioritize requirements.
• Conduct technical consultations and workshops to align AI solutions with business objectives.
• Act as the primary liaison between business teams and engineering teams throughout the delivery lifecycle.
• Present architectural recommendations, implementation approaches, and risk mitigation strategies to leadership.

Model Governance, Risk & Compliance

• Establish AI governance frameworks covering model lifecycle management, explainability, monitoring, and auditability.
• Ensure compliance with enterprise security standards, responsible AI practices, privacy requirements, and applicable regulations.
• Drive implementation of guardrails, human-in-the-loop controls, model evaluation, and risk management frameworks.
• Develop processes for model validation, performance monitoring, and regulatory adherence.

Engineering Excellence & SDLC Enablement

• Implement AI-assisted SDLC practices that improve team productivity, code quality, testing, documentation, and deployment efficiency.
• Create reusable AI accelerators, frameworks, and automation tools to enhance engineering productivity.
• Drive best practices for CI/CD, MLOps, LLMOps, model versioning, infrastructure automation, and release governance.
• Mentor development teams on AI engineering standards and operational excellence.

Production Deployment & Operations

• Lead deployment of AI solutions into production environments and ensure reliability, scalability, and observability.
• Monitor model performance, accuracy, latency, cost optimization, and user adoption metrics.
• Provide production support, incident resolution, root cause analysis, and continuous improvement.
• Manage AI application lifecycle from deployment through ongoing maintenance and enhancements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
• 10+ years of software engineering and architecture experience.
• 3+ years of hands-on experience with Generative AI, LLMs, and Agentic AI frameworks.
• Strong experience with OpenAI, Anthropic, Gemini, Azure OpenAI, AWS Bedrock, or equivalent AI platforms.
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
• Strong programming expertise in Python, Java, or related languages.
• Experience implementing AI/ML solutions in enterprise production environments.
• Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
• Knowledge of MLOps/LLMOps practices, model monitoring, and governance frameworks.
• Proven experience leading cross-functional teams and managing stakeholder expectations.

Preferred Qualifications

• Experience building Retrieval-Augmented Generation (RAG) solutions.
• Knowledge of vector databases such as Pinecone, Weaviate, Chroma, FAISS, or Azure AI Search.
• Experience with Responsible AI frameworks and AI governance programs.
• Certifications in Azure AI, AWS Machine Learning, Google AI, or related technologies.
• Experience in highly regulated industries such as Financial Services, Healthcare, Insurance, or Life Sciences.