About the Client
Our client is pioneering the Autopilot Enterprise, developing conversational AI agents that handle workflows, drive outcomes, and deliver measurable impact for businesses. They build autonomous, multilingual agents capable of complex reasoning, contextual understanding, and end-to-end workflow ownership, born from the belief that enterprises need a new playbook.
Role Overview
We are seeking an experienced and visionary Engineering Lead - ML to spearhead the development of next-generation conversational and dynamic AI agents. You will architect and scale systems that enable:
- Conversational Agents (Voice & Chat):
- Human-like, open-ended dialogues without rigid workflow design.
- Dynamic reasoning to achieve goals (e.g., selling a personal loan).
- Continuous self-learning from conversation outcomes.
- Operating at minimal latency and cost.
- Dynamic Workflow Agents:
- Agents that learn workflows (Sales, Support, Admin) by observing humans.
- Self-learning from live agent behavior, recordings, and transcripts.
- Ability to see, process/understand, reason, and interact with GUIs/browsers.
- One-shot learning from escalations, ensuring accurate human-AI collaboration.
- Human agent assist & copilot features driven by workflow context.
This is a rare opportunity to shape how enterprises adopt agentic AI, working directly at the intersection of AI research, applied ML, scalable infrastructure, and real-world enterprise workflows.
Key Responsibilities
Leadership & Vision
- Lead and mentor a team of engineers building agentic AI systems.
- Define technical vision, architecture, and product strategy.
Architecture & Delivery
- Design and scale enterprise-grade AI products leveraging reinforcement learning, computer vision, and LLM fine-tuning.
- Drive low-latency, cost-optimized systems in production.
- Ensure robust engineering standards, testing, and security practices.
Innovation & Integration
- Develop pipelines for self-learning agents from conversations and human workflows.
- Architect systems for human-in-the-loop escalation and AI copilots.
- Collaborate with product, design, and research teams to deliver real-world outcomes.
Operational Excellence
- Establish CI/CD pipelines, automation, and best practices.
- Proactively identify risks and resolve technical challenges.
- Optimize for scalability, reliability, and enterprise integration.
What We’re Looking For
- Experience: 6-10 years of experience.
- AI/ML Skills: Strong expertise in Reinforcement Learning, Computer Vision, LLM fine-tuning, and applied ML research.
- Systems Expertise: Proven ability to build and scale large-scale distributed systems and enterprise-grade products.
- Infrastructure Skills: Deep understanding of cloud platforms (AWS, GCP, Azure) and scalable architecture.
- Hands-on Engineering: Proficiency in Python, Go, Java, or equivalent languages.
- Mindset: Passion for building product-first AI systems (not services), strong execution ability, and innovation-driven leadership.