Developer - AI

Overview Software Engineer (Developer 2 ) C++ and AI-Centric Engineering Focus 📍 Location: Hyderabad, India | Hybrid – 3 Days in the Office About The Role We’re looking for a hands-on Software Engineer with strong C++ fundamentals and a growing interest in applied AI for enterprise software modernization. In this role, you’ll build secure, reliable backend services and contribute to AI-enabled capabilities that improve automation, developer productivity, and product intelligence across Hyland’s enterprise platforms.

You’ll work in a collaborative engineering team — writing production-quality C++ code, participating in design discussions, and using AI-assisted development responsibly. Python and Java or C# exposure is helpful for tooling, automation, and integration work, but the primary expectation is strong C++ engineering discipline and an interest in picking up C# skills.

Your Role Responsibilities? Here’s What You’ll Do.

• Design, develop, test, and maintain enterprise software components using modern C++ (C17/C20), with focus on memory safety, performance, concurrency, reliability, and maintainability across Hyland’s enterprise platforms.
• Contribute to AI-assisted development practices using tools such as GitHub Copilot, Cursor, or Claude — while maintaining peer review, testing, security, and code-quality standards to ensure responsible and validated use of AI-generated code.
• Participate in technical design reviews, code reviews, and debugging sessions, applying strong object-oriented design, data structures, algorithms, and systems fundamentals to deliver scalable and maintainable solutions.
• Troubleshoot moderate to complex production issues, analyze performance bottlenecks, and improve system reliability in cloud and containerized environments using Docker, Kubernetes, AWS, or Azure.
• Use secondary languages such as Python and Java or C# where needed for scripting, automation, integration utilities, or interoperability with existing enterprise systems and services.
• Collaborate with cross-functional engineering teams to contribute to backlog prioritization, work estimation, and continuous improvement of development processes, tooling, and delivery pipelines using Azure DevOps and GitHub.

Technology Tools You’ll Use Primary Language

• Modern C++ (C17 / C20, STL, memory management, concurrency, performance profiling)

Secondary Language Exposure

• Java or C# (integration with existing enterprise services)
• Python (scripting, automation, and integration utilities)

AI-Assisted Development Tools

• GitHub Copilot, Cursor, Claude, LLM APIs & Prompt Engineering Basics

APIs & Data Technologies

• REST APIs, SQL & NoSQL Databases, MongoDB, PostgreSQL, Elasticsearch

Containerization & Orchestration

• Docker, Kubernetes Fundamentals

Cloud & DevOps Platforms

• AWS or Azure Cloud Services, Azure DevOps, GitHub, CI/CD & Automated Testing Frameworks

Messaging & Streaming

• Apache Kafka

Role Essentials

• 4–7 years of software engineering experience, with at least 3 years of hands-on production development and a strong foundation in modern C++ (C17/C20) — including object lifetimes, memory management, templates, concurrency, exception safety, debugging, and performance optimization.
• Proven experience building APIs, services, and distributed application components with secure coding practices, automated testing, and maintainable design patterns in cloud and enterprise environments using AWS or Azure.
• Strong understanding of object-oriented design, data structures, algorithms, and systems fundamentals, with the ability to participate meaningfully in technical design reviews, code reviews, and debugging sessions across complex enterprise software systems.
• Exposure to AI-assisted development or AI-enabled product features, including responsible use of code generation tools such as GitHub Copilot, Cursor, or Claude, basic prompt engineering, and the ability to validate, review, and maintain AI-generated code to production standards.
• Strong oral and written communication skills with a collaborative mindset; demonstrated ability to work effectively within Agile product development teams, contribute to backlog prioritization, and drive continuous improvement across engineering processes and delivery pipelines.

What We’d Like to See

• Exposure to LLM APIs, embeddings, RAG concepts, vector databases, or AI-powered search …