Experienced Software Developer

AVEVA•Philadelphia, PA

1d•$124,200 - $236,900•Hybrid

About The Position

AVEVA is creating software trusted by over 90% of leading industrial companies. As an Experienced Software Developer, your responsibilities will include recognizing, articulating, and making technical decisions / trade-offs around multiple dimensions (scaling, reliability, performance, maintenance, etc.) that have an impact on your team. You will be responsible for designing, developing, testing, debugging, and maintaining high-quality software applications and cloud-native services. Building scalable, fault-tolerant solutions on Microsoft Azure using modern cloud architecture and engineering best practices is a key aspect of this role. You will also be designing and implementing microservices, REST APIs, and distributed systems that support enterprise-scale applications. Developing AI-enabled solutions by integrating Large Language Models (LLMs) into enterprise applications while evaluating trade-offs between performance, cost, latency, and model capabilities is also a significant part of the position.

Requirements

Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, Physics, Electrical, Mechanical, or Chemical Engineering, or a related technical field, or equivalent practical experience.
5+ years of professional software development experience building enterprise applications using object-oriented programming languages such as C#, .NET, C++, or JavaScript.
Demonstrated ownership of medium-to-large engineering initiatives from design through deployment with minimal supervision.
Strong experience designing and building microservices, REST APIs, and distributed systems.
Experience developing cloud-native applications on Microsoft Azure (AWS or Google Cloud experience is also valuable).
Strong understanding of SQL and NoSQL databases and designing scalable data architectures.
Experience working with Large Language Models (LLMs) and understanding the trade-offs between model capability, latency, scalability, and operational cost.
Hands-on experience designing or implementing Retrieval-Augmented Generation (RAG) solutions.
Experience with AI standards and frameworks such as Model Context Protocol (MCP), Agent2Agent (A2A), Semantic Kernel, Microsoft AI Foundry, or Microsoft Agent Framework (MAF).
Experience with graph technologies, including GraphRAG, graph databases, knowledge graphs, ontologies, and semantic data modeling concepts to support AI-driven solutions.
Experience evaluating AI outputs, including automated testing, validation, and quality measurement techniques.
Experience building and integrating enterprise AI applications using Kubernetes, Docker, CI/CD, and DevOps best practices.
Experience working in Agile/Scrum environments with Infrastructure as Code (IaC) and modern cloud-native development practices.
Excellent communication, collaboration, and problem-solving skills with the ability to explain complex technical concepts to both technical and non-technical audiences.

Nice To Haves

AWS or Google Cloud experience is also valuable.
Experience designing and developing in C#/.NET framework

Responsibilities

Recognizing, articulating, and making technical decisions / trade-offs around multiple dimensions (scaling, reliability, performance, maintenance, etc.) that have an impact on your team.
Designing, developing, testing, debugging, and maintaining high-quality software applications and cloud-native services.
Building scalable, fault-tolerant solutions on Microsoft Azure using modern cloud architecture and engineering best practices.
Designing and implementing microservices, REST APIs, and distributed systems that support enterprise-scale applications.
Developing AI-enabled solutions by integrating Large Language Models (LLMs) into enterprise applications while evaluating trade-offs between performance, cost, latency, and model capabilities.
Designing Retrieval-Augmented Generation (RAG) solutions and leveraging GraphRAG techniques to improve contextual accuracy and knowledge retrieval.
Implementing AI orchestration frameworks and agent-based architectures using technologies such as Semantic Kernel, AI Foundry, Microsoft Agent Framework (MAF), Model Context Protocol (MCP), and Agent2Agent (A2A).
Applying prompt engineering techniques, tool calling, and agent orchestration to build intelligent, production-ready AI applications.
Working with graph technologies and applying knowledge graph and ontology concepts to enhance AI-driven solutions.
Delivering software on time while providing accurate estimates and consistently meeting delivery commitments.
Understanding and proactively following team processes, engineering best practices, documentation standards, and code quality guidelines.
Being persistent in resolving technical challenges, collaborating with cross-functional teams when necessary to drive solutions.
Providing technical support for products, including troubleshooting complex customer issues and production escalations.
Communicating technical designs through architecture documentation, design reviews, and technical presentations.
Providing thoughtful feedback during code reviews, architecture discussions, and engineering design sessions.
Continuously expanding knowledge of modern software engineering practices, cloud technologies, AI frameworks, and emerging industry trends.
Mentoring junior developers by providing technical guidance, coaching, and support to help them grow professionally.
Taking an active role in recruiting, interviewing, and onboarding new engineering talent.