Embed within client engineering teams and contribute directly to the design, development, deployment, and support of production-grade applications and AI-powered solutions
Drive end-to-end software delivery, from requirements gathering and solution design to implementation, testing, deployment, and post-production support
Operate as a senior engineering resource within client environments, ensuring high-quality and timely execution
Leverage AI-assisted development tools such as Claude Code, Cursor, OpenAI Codex, GitHub Copilot, or equivalent platforms as an integral part of the software development lifecycle
Develop and promote reusable prompt engineering practices, AI workflows, and productivity-enhancing development patterns
Evaluate AI tools and provide recommendations on their effective usage, limitations, and validation requirements
Serve as a trusted technical advisor by providing guidance on architecture, scalability, security, performance, and engineering best practices
Translate business requirements into practical technical solutions and lead technical design discussions and architecture reviews
Establish and uphold coding standards, quality assurance practices, and engineering excellence across engagements
Build strong relationships with client stakeholders, including engineering leaders, product teams, and executive sponsors
Identify opportunities to expand client engagements by uncovering additional business needs and recommending value-driven solutions
Support technical presentations, solution discussions, and strategic conversations that contribute to account growth
Contribute reusable frameworks, accelerators, AI workflows, prompt libraries, and best practices to QBurst’s internal knowledge repository
Mentor team members and promote the adoption of modern engineering and AI-enabled development practices
Stay current with emerging technologies, AI advancements, and industry trends to continuously enhance delivery capabilities
Requirements
5+ years of hands-on software engineering experience delivering enterprise-grade applications in production environments
Proven experience delivering at least two complete software development lifecycles, from solution design through deployment and ongoing support
Demonstrated daily use of AI-assisted development tools such as Claude Code, GitHub Copilot, Cursor, Codex, or equivalent platforms in a professional setting
Proficiency in at least two programming languages, with expertise spanning backend, frontend, or data engineering technologies
Hands-on experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform, including deployment, configuration, monitoring, and troubleshooting
Strong understanding of APIs, microservices architectures, CI/CD pipelines, and modern software development methodologies
Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences, including executive stakeholders
Proven ability to manage client expectations, navigate critical incidents, and maintain stakeholder trust in demanding environments
Strong consulting mindset with the ability to balance technical excellence and business outcomes
Prior experience as a Forward Deployed Engineer, Solutions Engineer, Technical Consultant, or in a client-facing engineering role is preferred
Experience building AI agents and workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies is desirable
Professional certifications such as AWS Professional, Azure Solutions Architect Expert, TOGAF, or AI/ML specialty certifications are a plus
Exposure to pre-sales activities, including solution discovery, estimation, proposal development, and technical presentations, is advantageous
