About the role

Senior Software Engineer developing scalable backend systems at PDI Technologies for convenience retail. Collaborating with cross-functional teams to improve business outcomes with modern application development.

Responsibilities

Lead system design and technical implementation for complex features, with emphasis on reliability, performance, maintainability, and security.
Develop and enhance cloud-native solutions using AWS and modern deployment practices such as CI/CD, containerization, and observability.
Integrate AI and generative AI capabilities into products and platforms, including intelligent workflows, automation, and context-aware user experiences.
Collaborate with product managers, UX, architects, and operations teams to translate business needs into production-ready technical solutions.
Mentor junior engineers through code reviews, design guidance, and engineering best practices.
Drive continuous improvement in software quality, development standards, operational readiness, and technical documentation.
Contribute to troubleshooting, performance optimization, and root-cause analysis across development and production environments.
Design and build scalable enterprise applications, backend services, and APIs that support high-availability workloads.

8+ years of software engineering experience, with demonstrated success delivering production-grade applications and backend systems.
Strong backend development experience using technologies such as .NET / C#, Java, Python, or similar server-side platforms.
Hands-on experience with SQL Server or other relational databases, including schema design, query optimization, and data access patterns.
Proven experience building scalable APIs, microservices, and distributed systems.
Strong knowledge of software engineering fundamentals, including object-oriented design, testing, code quality, and secure development practices.
Experience working in cloud environments, with AWS preferred.
Strong communication, collaboration, and problem-solving skills, with the ability to work effectively in agile engineering teams.
Experience integrating AI / ML or generative AI capabilities into software products and business workflows.
Working knowledge of Large Language Models (LLMs), prompt design, retrieval-augmented generation (RAG), and AI service orchestration.
Familiarity with building intelligent assistants, workflow automation, recommendation features, or agent-based systems.
Understanding of vector databases, embeddings, semantic search, and data pipelines that support AI-driven experiences.
Awareness of responsible AI practices, including evaluation, monitoring, safety, privacy, and governance considerations.