Sr. AI ML Engineer

6 to 9 years of experience across software engineering, machine learning, or applied AI roles. - Proven experience leading engineering teams while remaining hands-on in implementation. - Proven experience delivering production AI projects. - Strong programming skills in Python. - Strong backend engineering fundamentals with FastAPI, API design, async workflows, and service orchestration. - Strong understanding of supervised learning, unsupervised learning, model evaluation, and practical ML problem solving. - Strong experience with LLMs, prompt engineering, RAG systems, agentic workflows, and LLM application architecture. - Strong experience with fine-tuning and model adaptation strategies. - Strong experience delivering computer vision systems in production environments. - Strong experience with voice AI workflows, including speech-to-text and text-to-speech systems. - Strong understanding of production architecture, deployment, monitoring, logging, debugging, and reliability. - Strong analytical and problem-solving ability. - Experience working with cloud infrastructure and production deployments. - Strong understanding of engineering quality, security, access control, and maintainability patterns. In summary, as a Lead AI Engineer at MSBC Group, you will play a crucial role in designing, delivering, and scaling production-grade AI systems while leading a team of engineers and ensuring technical excellence and client satisfaction. As a Lead AI Engineer at MSBC Group, your role involves owning client-facing AI solutioning, managing and mentoring a growing engineering team, and personally delivering production-grade systems across various applications such as LLMs, multi-agent systems, voice AI, computer vision, backend orchestration, and analytics. You will be responsible for leading the end-to-end delivery of AI solutions, managing and mentoring an initial team of 5 to 6 engineers, and remaining hands-on in engineering, architecture, code reviews, and technical problem-solving. Your main responsibilities include:

Leading the end-to-end delivery of AI solutions from discovery and technical scoping through development, testing, deployment, and iteration. - Managing and mentoring an initial team of 5 to 6 engineers while building strong delivery practices, code quality standards, and engineering culture. - Remaining hands-on in engineering, architecture, code reviews, and technical problem-solving across AI and backend systems. - Designing and delivering production-ready applications across various AI applications. - Architecting scalable backend services and APIs using Python. - Owning solution architecture for client-qualified opportunities after sales handoff, including discovery calls, solution design, technical scoping, and demo presentations. - Translating business problems into practical AI solutions with clear delivery plans, trade-offs, and implementation paths. - Establishing best practices across testing, deployment, monitoring, performance optimization, observability, security, and main