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# EY-Parthenon - Strategy and Execution - Growth Platforms - Software Engineer - Sr Assoc/Consultant

- **Company:** Ernst & Young LLP
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $130,000.0 - $185,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Layers, Computing Platforms, Automated Storage and Retrieval Systems, Cloud Engineering, Software Quality, Continuous Integration, Decision Support Systems, Programming Tools, Distributed Systems, Python (Programming Language), Cloud Services, Microsoft Copilot, Scala (Programming Language), Software Engineering, Software Systems, TypeScript, Software Organization, Application Enhancement Tool, Large Language Models, Backend, Agentic-AI, Event Driven Architecture, AI Platforms, Build Tools, GPT
- **Published:** October 23, 2026
- **Apply:** https://www.atlantacareerpath.com/job.asp?id=3466667976&tx=VT7166THI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Successful candidates will bring strong engineering judgment, fluency in modern AI tooling, and the ability to operate comfortably across strategy and execution., * Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.

 * Strong proficiency in modern software development practices, including APIs, distributed systems, and cloud services.
 * Hands-on experience deploying AI-enabled applications or tooling into production environments.
 * Comfort operating in fast-paced, client-facing environments with evolving requirements.
 * You must either reside in or be in a commutable distance to your office location for this position.
 * The ability and willingness to travel and work in excess of standard hours when necessary. In certain circumstances, travel may be required beyond your work location based on client and project needs.

Ideally, you will have

 * Experience working in management consulting, product-led organizations, or high-growth startups.
 * Familiarity with modern AI ecosystems, including LLM frameworks, agent architectures, and prompt/tool orchestration.
 * A strong product mindset-understanding not just how to build systems, but how they will be adopted and sustained.
 * Knowledge of how to leverage firm-approved AI tools in a business setting, including Microsoft Copilot.

What we look for

We are looking for candidates who have a strong aptitude for quantitative and qualitative analysis and the ability to link business strategy to performance. Being a strong team player is critical with the ability to adapt to changing requirements or deadlines in support of our clients' goals.

## Description

As a Software Engineering Senior Associate/Consultant, you will assist in the design and delivery of production-grade software systems and AI-enabled tooling that underpin high-visibility client engagements and internal platforms., * Architect, build, and scale core software platforms that integrate data, AI services, and user-facing applications.

 * Assist in the development of AI-powered tools, including decision support systems, copilots, internal developer tools, and domain-specific agents.
 * Design and maintain robust service architectures (APIs, event-driven systems, batch and real-time pipelines) optimized for reliability, security, and extensibility.
 * Establish engineering best practices across code quality, testing, CI/CD, observability, and performance.
 * Collaborate with AI/ML engineers to productionize models and agents, ensuring seamless integration into real-world workflows., * Assist in the development of backend and full-stack systems using modern languages and frameworks (e.g., Python, Java, Scala, TypeScript).
 * Design and manage cloud-native architectures on platforms such as AWS or GCP, using containerization and infrastructure-as-code.
 * Build AI-ready application layers that integrate LLMs, retrieval systems, vector databases, and model orchestration frameworks.
 * Develop internal tooling and developer platforms that improve velocity, reliability, and reuse across teams.
 * Define and enforce standards for security, privacy, reliability, and compliance (e.g., SOC2, HIPAA, enterprise governance).
 * Translate ambiguous business problems into concrete system designs and incremental delivery plans.
 * Communicate complex technical concepts clearly to non-technical stakeholders.