Responsibilities

• 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

• 5–8 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