AI Engineer - Hybrid at A.C. Coy

Pittsburgh, Pennsylvania, United States -

Full Time

Start Date

Immediate

Expiry Date

28 May, 26

Salary

0.0

Posted On

27 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Agentic Solutions, MLOps, CICD, Prompt Templates, Model Evaluation, Red-Teaming, NIST AI Risk Management Framework, Python, Java, Linux, Node.js, APIs, Vector Databases, RAG, AWS Bedrock

Industry

Information Technology & Services

Description

Overview Location: 3/2 Hybrid arrangement; Office located in downtown Pittsburgh, PA Type: Direct Hire Work Authorization: US Citizen or Green Card holder only; Visa Sponsorship not available 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. 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 Qualifications 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

The AI Engineer will be responsible for designing, building, deploying, certifying, and maintaining production-grade generative AI and agentic business solutions. This includes advancing the AI strategy, collaborating with stakeholders, and leading the full-stack end-to-end development of custom AI solutions.