Sr. Software Engineer Lead

Description

Design, build, deploy, and support secure cloud-based applications and services that meet business and customer requirements.
- Develop and maintain both front-end and back-end components of modern web applications using React, TypeScript, Python, SQL, and related technologies.
- Build scalable APIs, integrations, and data-driven applications using modern engineering practices.
- Leverage AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and delivery velocity.
- Support the integration of AI capabilities, including LLMs, Generative AI services, AI agents, and intelligent automation features, into existing and new business applications.
- Contribute to the development, integration, testing, deployment, and support of AI-enabled solutions, including Retrieval-Augmented Generation (RAG), intelligent search, conversational experiences, and workflow automation capabilities.
- Assist with the implementation and operationalization of agentic AI solutions, including prompt engineering, tool integration, vector search, and orchestration frameworks under the guidance of senior technical leaders.
- Collaborate with product owners, business stakeholders, architects, and engineering teams to deliver scalable end-to-end solutions supporting reporting, analytics, dashboarding, and business process automation initiatives.
- Participate in all phases of the software development lifecycle, including requirements analysis, solution design, development, testing, deployment, and production support.
- Apply Agile and Lean development practices to deliver features and enhancements within established timelines and quality standards.
- Participate in code reviews, technical design discussions, and continuous improvement activities to promote engineering excellence and software quality.
- Build and support cloud-native solutions utilizing Azure services, including Azure OpenAI, Azure AI Search, Azure Functions, Service Bus, and related platform capabilities.
- Support CI/CD automation, Infrastructure as Code initiatives, containerized deployments, and DevOps practices utilizing GitHub, Docker, Kubernetes, and Terraform.
- Troubleshoot application, integration, and performance issues, identify root causes, and implement sustainable solutions.
- Monitor and support production applications while meeting operational, reliability, and service-level objectives.
- Collaborate effectively with cross-functional and global teams to deliver business value and technical solutions.
- Continuously learn and apply emerging AI, cloud, and software engineering technologies to improve team effectiveness and accelerate solution delivery.
Qualifications

Graduate degree or equivalent experience.
Required Qualifications
•Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
•7+ years of experience with Agile/Lean software development practices.
•4+ years of experience with cloud environments and architecture, preferably Azure.
•Experience automating CI/CD pipelines and working with source control systems such as Git and GitHub.
•Hands-on experience with JavaScript, TypeScript, React, SQL databases, and modern web application development.
•Strong experience developing applications and services using Python and modern API development practices.
•Experience building and supporting scalable, secure enterprise-grade applications using modern architecture patterns, microservices, and service-oriented architectures.
•Experience working with Docker, Kubernetes, and cloud-native application deployment practices.
•Experience building infrastructure using Infrastructure as Code, preferably Terraform.
•Demonstrated use of AI-assisted development tools to improve engineering productivity, software quality, testing, documentation, and development velocity.
•Some hands-on experience designing, developing, and deploying applications that integrate Large Language Models (LLMs), Generative AI services, AI agents, or intelligent automation capabilities.
•Familiarity with AI application patterns such as Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, semantic search, conversational AI, or knowledge-grounded AI solutions.
•Experience consuming and integrating AI platform capabilities such as Azure OpenAI, Azure AI Search, Azure Functions, and related Azure services.
•Familiarity …