Lead Software Development Engineer - Data Engineering

About the Role 

• As a Lead Gen-AI & AI/ML Engineer, you will lead the design and engineering of advanced 
• agentic AI systems, drive architecture decisions, and guide a team toward delivering 
• high-impact AI solutions. You will be responsible for scaling AI/ML capabilities across the 
• organization, owning production-grade deployments, and ensuring that our agentic platforms 
• are robust, secure, and aligned with business goals. This is a leadership role requiring deep 
• technical expertise as well as team management experience. 
• Key Responsibilities

Strategic Ownership & Architecture 

• ● Own the architecture of enterprise-grade agentic AI systems and multi-agent workflows. 
• ● Define engineering best practices and guide technical decisions across Gen-AI, ML, and 
• automation initiatives. 
• ● Evaluate emerging AI research and technologies for integration into platforms and 
• products. 
• ● Lead cross-functional discussions with engineering, product, business, and data teams. 
• Agentic Systems & MCP Infrastructure 
• ● Architect goal-driven agent frameworks capable of reasoning, planning, and taking 
• autonomous actions. 
• ● Build and evolve Model Context Protocol (MCP) infrastructure for secure, context-rich 
• interactions with tools, APIs, databases, and cloud systems. 
• ● Oversee design of long-running, stateful agent pipelines with strong error recovery, 
• coordination strategies, and dynamic task management. 

Advanced AI/ML Engineering 

• ● Lead the development of ML/DL models, including generative models, multimodal 
• pipelines, and retrieval-augmented architectures. 
• ● Ensure scalable, observable, and reliable ML operations (MLOps/LLMOps) across the 
• lifecycle. 
• ● Guide teams in model evaluation, benchmarking, optimization, and production 
• deployment. 
• Human-in-the-Loop & Continuous Learning Systems 
• ● Design and supervise RLHF processes, feedback loops, and reward modeling 
• frameworks. 
• ● Ensure systems evolve through continuous human feedback and real-world interactions. 

Team & Project Ownership 

• ● Manage and mentor AI/ML engineers, helping them grow in agentic reasoning, model 
• development, and production engineering. 
• ● Lead project planning, estimations, reviews, and cross-team execution. 
• ● Drive a culture of experimentation, innovation, and high engineering excellence.