AI Engineer - Hybrid

A.C. Coy•Pittsburgh, PA

16h•Hybrid

About The Position

A.C.Coy is assisting a local client in their search for a full-time AI Engineer. This individual will be responsible for designing, building, deploying, certifying, and maintaining production-grade generative AI and agentic business and technology solutions. This high-profile role will have an excellent salary and benefits package, as well as numerous professional development opportunities and the potential for a substantial bonus.

Requirements

10 years of overall experience in software engineering, data science, or related technical roles, with strong proficiency in coding, business and system design, and production deployment
A minimum of 1-2 years of hands-on experience building and deploying generative AI solutions in enterprise environments
Bachelor’s degree in Artificial Intelligence, Data Science, or related field or an equivalent combination of education and work experience
Proficient in backend development using AI algorithms
Proficiency with Python, Java, Shell, Linux or Node.js, MCP, APIs, knowledge graphs, vector databases, & data structures
Demonstrated knowledge of MLOps, model lifecycle, and (CI/CD) practices
Experience designing and implementing full-stack AI solutions using modern MLOps and AI frameworks (e.g RAG) and platforms such as GitHub Agent, Snowflake agents, Copilot Studio and AWS Bedrock
Experience creating reusable frameworks, prompt templates, and reference architectures to accelerate AI solution delivery across teams

Responsibilities

Advance the organization’s AI strategy with a strong emphasis on identifying high- value opportunities, defining technical roadmaps, prioritizing use cases, and advocating for responsible, extensible and scalable IA adoption
Collaborate with business and IT stakeholders to deeply understand current state processes and workflows in order to deliver AI powered solutions that deliver high-impact solutions driving measurable operational efficiency and transformation
Lead the full stack end-to-end development of custom AI solutions leveraging knowledge of MLOps, context management, and CICD practices to orchestrate AI agents and technology (e.g., Copilot AI, Snowflake AI, GitHub AI, AWS Bedrock, etc)
Design, create, and implement reusable AI frameworks, prompt templates, reference architecture, and reference architectures to accelerate AI solution delivery across teams
Support the model evaluation, testing, and certification process: red-teaming, bias/fairness testing, accuracy benchmarking, hallucination detection, content safety filtering, and production readiness sign-off in regulated environments
Establish and enforce responsible AI governance practices, including aligning to the NIST AI Risk Management Framework
Collaborate with cloud, data and security architecture teams to build secure, extensible solutions
Stay current with the latest capabilities in current and emerging AI agentic technology and frameworks
Experiment with alternative AI models and enhance the organization's overall AI technology capabilities
Provide guidance on feasibility, risks and expected business impacts of AI initiatives
Evaluate third party application’s AI capabilities to ensure the usage is aligned with the organization's risk appetite
Draft clear documentation for AI models, data flows, AI solutions, APIs and operational procedures