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.