Experienced Software Developer

AVEVA is creating software trusted by over 90% of leading industrial companies.

Salary Range:

$124,200.00 - $236,900.00

This pay range represents the minimum and maximum compensation that the position offers, and final compensation can vary within the range depending on work location, job experience, skills, and relevant educational attainment and/or training. 

Position: Experienced Software Developer

Qualifications: Experience designing and developing in C#/.NET framework

Employment type: Full-time regular (flexible working options available)

Location: Philadelphia, PA – Hybrid

Benefits: Competitive salary; 20 Vacation days with increase for time served; high quality healthcare; 401(k) with 6% employer match; FSA and supplemental insurance; paid parental leave; 3 days paid volunteering; summer Fridays; flexible lifestyle benefits (fitness/tuition reimbursement)

 

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.

• 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.

Required Skills:

• 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.

• 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