Job Title: AI-Native Staff Engineer
Location: Blue Bell, PA
End Client: Cotiviti USA, LLC (US - Local)
Branch / Location: Blue Bell, PA
Position Type: Contract (C2C)
Position Description & Objectives
This role operates within an AI-native delivery model where engineers leverage tools like Claude to generate, review, and refine large volumes of production-bound code across the full stack.
The Staff Engineer (AI) acts as a senior individual contributor who also guides a small team, building production software using AI-native development workflows as part of an agile, focused AI-Native team.
Note: This role is NOT focused on training AI models or building machine learning pipelines. The core focus is building software efficiently, safely, and at high quality using AI-assisted engineering practices.
Key Responsibilities
AI-Native Software Development: Build and enhance production-grade software applications, translating product and technical requirements into maintainable software using AI tools to accelerate coding, debugging, testing, refactoring, and documentation.
Application Design & Implementation: Design and implement clean, well-structured APIs, services, and application components across scalable backend systems and full-stack solutions.
AI Orchestration & Workflow Execution: Orchestrate the effective use of AI tools (code generation, refactoring, test creation, validation, debugging) while adhering to and helping refine engineering standards established by the Tech Lead.
Collaboration & Team Execution: Coordinate closely with AI-Native Tech Architects and adjacent teams to deliver features end-to-end and clearly communicate technical tradeoffs.
Required Skills & Qualifications
Primary Skills: Java, Database Design (Oracle, PostgreSQL), AI-Tooling & Prompt Orchestration (Claude, GitHub Copilot, or equivalent).
Secondary / Additional Skills: Git, Docker, AWS, Full-stack development practices, automated testing frameworks, and API architecture.
Core Competencies:
Strong background in backend/full-stack software engineering.
Proven experience integrating AI coding assistants natively into daily development life cycles.
Ability to rigorously review, validate, and refine AI-generated code for correctness, performance, and security.