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# AI Engineer

- **Company:** Precision Castparts Corp.
- **Location:** Clackamas, OR, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Audit Trail, Microsoft Azure, Cloud Database, Software Quality, Continuous Integration, Data as a Services, Extract Transform Load (ETL), Data Structures, Database Applications, Design of User Interfaces, Python (Programming Language), Machine Learning, Node.Js, Performance Tuning, Software Engineering, SQL Databases, Web Applications, Enterprise Software Applications, Cloud Platform System, ReactJS, Flask (Web Framework), Snowflake, Software Application Programming, Agentic-AI, Git, Event Driven Architecture, Build Management, AngularJS, Information Technology, Low Latency, Operational Systems, Restful APIs, Streamlit Framework, Automation Anywhere, Databricks, Microservices
- **Published:** October 19, 2026
- **Apply:** https://pcctalentacquisitionportal.tal.net/vx/lang-en-GB/mobile-0/appcentre-1/brand-7/candidate/so/pm/1/pl/3/opp/24724-AI-Engineer/en-GB

## About the Role

* 2+ years' experience in software development, application engineering, or full-stack development
 * Bachelor's or Master's degree in computer science, software engineering, or a related field (or equivalent experience)
 * Preferred experience building web-based or data-driven applications in cloud environments (AWS, Azure, or GCP)
 * Experience integrating APIs and developing UI/UX for data and AI-enabled tools
 * Preferred certifications: AWS Developer Associate, or Azure App Developer, * Proficiency in Python and Javascript
 * Proficiency building applications using common Python or Node.js frameworks (Streamlit, Dash, Gradio, Shiny, Flask, React, Angular, etc.)
 * Familiarity with AI/ML concepts and ability to integrate model outputs into apps or workflows
 * Prefer AWS AI/ML experience such as Bedrock and SageMaker and/or Azure tools like Azure Cognitive Services/Foundry
 * Prefer experience developing Databricks Apps or similar modular, cloud-hosted applications
 * Strong understanding of RESTful APIs, microservices, and event-driven architectures
 * Proficiency with CI/CD pipelines, Git, and agile software delivery
 * Familiarity with ETL pipelines and data modeling frameworks
 * Experience with SQL and cloud databases (e.g., Snowflake, Redshift, or Databricks SQL)
 * Strong focus on usability, code quality, and maintainability
 * Good understand of data algorithms, data structures, and performance tuning.
 * Excellent collaboration and communication skills, with a proactive, product-focused mindset

## Description

The AI Engineer is responsible for designing, developing, and deploying AI-driven workflows and applications to address complex business and engineering problems. The role will primarily leverage Databricks Apps and the PCC data platform, using common Python or Node.JS frameworks such as Streamlit, Dash, and Gradio. This role combines strong software engineering fundamentals with hands-on AI/ML expertise helping teams build intelligent systems that streamline operations, automate analysis, and enhance decision-making. You will collaborate with data scientists, analysts, production teams, engineering, and business leaders to take AI solutions from early concepts and prototypes through production deployment and measurable business outcomes. This is a hands-on role from someone who understands how AI systems behave, fail and how to engineer reliable solutions., * Design and build AI-powered workflows ("AI Agents") and apps using Databricks.

 * Build AI agents and intelligent workflows that reason, use tools, interact with enterprise applications and data, and execute complex multi-step processes with appropriate human oversight.
 * Translate business requirements into technical designs, user stories, and functional specifications for assigned workstream. Shape how models learn, reason, and perform with real world business input.
 * Evaluate data patterns and system behavior to inform solution improvements and implementation decisions.
 * Evaluate and select models and solution approaches based on quality, reliability, latency, cost, security, scalability, and business requirements, and develop systematic evaluation cases to measure solution performance.
 * Integrate APIs, model endpoints, and data services into user-facing tools and operational systems.
 * Write, review and refining code in collaboration with data scientists to productionize models and embed them into functional business apps.
 * Ensure performance, reliability, and scalability of AI workflows in cloud environments.
 * Contribute to enterprise AI governance and compliance frameworks (e.g., model lineage, permissions, auditability)