Custom Software Engineer

About the Role

• Develop custom software solutions to design, code, and enhance components across systems or applications.
• Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
• Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks.
• Drive innovation, efficiency, and business transformation.
• Lead AI-driven solution design and delivery by applying GenAI and Agentic AI to address complex business challenges, automate processes, and integrate intelligent insights into enterprise workflows for measurable impact.

Key Responsibilities

• Hands-On Coding: Actively develop, test, and deploy application-heavy solutions. Write clean, efficient code in .NET Core (C#, ASP.NET), and Python for backend systems. Contribute to front-end development using React or Angular.
• Solution Design: Partner with senior architects to design scalable, cloud-native application architectures, focusing on performance, maintainability, and integration in multi-cloud environments.
• Integration Development: Build and maintain integrations using APIs, microservices, and event-driven patterns (e.g., REST, GraphQL, Kafka, or message queues).
• Multi-Cloud Implementation: Develop and deploy applications across AWS, Azure, and Google Cloud, ensuring portability and optimization for cost and performance.
• AI Integration: Implement practical AI features (e.g., automation, basic analytics) using cloud-based AI services or frameworks like TensorFlow or PyTorch.
• Infrastructure Support: Collaborate with DevOps teams to implement containerized solutions (Docker, Kubernetes) and CI/CD pipelines, with hands-on use of IaC tools like Terraform or BiCep.
• Performance Security Optimization: Ensure applications meet performance and security standards through code reviews, testing, and adherence to best practices.
• Team Collaboration: Work closely with developers, product managers, and infrastructure teams to translate requirements into technical implementations, providing hands-on support and mentorship.
• Continuous Learning: Stay updated on full-stack development trends, cloud technologies, and AI advancements to contribute to innovative solutions.

Requirements & Tech Stack

• Must have skills: .Net Full Stack Development
• Professional Technical Skills:
• Strong grasp of Generative and Agentic AI, prompt engineering, and AI evaluation frameworks.
• Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization.
• Robust experience in .NET Core, MVC, and Python.
• Working knowledge of front-end technologies like React or Angular.
• Foundational understanding of AI integration.
• Experience building and deploying solutions in multi-cloud environments (AWS, Azure, Google Cloud).
• Hands-on experience with integration patterns (e.g., REST APIs, message queues) and microservices architecture.
• Familiarity with infrastructure tools like Docker, Kubernetes, and IaC (e.g., Terraform, BiCep).
• Experience with cloud-native services (e.g., Azure Functions, LogicApps, ServiceBus).
• Working knowledge of DevOps practices, including CI/CD pipelines and monitoring tools.
• Understanding of secure coding practices and basic enterprise security standards (e.g., IAM, encryption).
• Good to have skills: NA

Qualifications

• Skills:
• 5 to 12 years of hands-on experience in full-stack development.
• At least 2 years in a lead developer or junior architect role focusing on application-heavy systems.
• Basic exposure to AI/ML integration, such as using cloud AI services (e.g., Azure Open AI, Azure Foundry, AWS SageMaker,) or simple ML frameworks.
• Soft Skills:
• Strong debugging and problem-solving skills with a hands-on mindset.
• Clear communication to collaborate with technical and non-technical stakeholders.
• Ability to juggle hands-on coding with architectural design contributions.
• Eagerness to learn and adapt to new tools, frameworks, and cloud technologies.
• Education:
• Bachelors degree in computer science, Engineering, or a related field.
• 15 years full time education
• Certifications like Azure Developer Associate, Azure AI Fundamentals or similar are a plus.