Lead Software Development Engineer - Data Engineering

Role description

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.