Lead AI Engineer

About Deep AI Lab

Deep AI Lab is building the future of enterprise work. We’re creating an enterprise knowledge-grounded, compliance-centric, agentic AI platform — a powerful AI companion designed to empower knowledge workers across enterprises.

Founded in late 2024 by top-notch generative AI experts, technology visionaries, and veteran product leaders, and combining deep technical expertise and proven enterprise product vision. Our platform blends AI orchestration, governance, and knowledge intelligence to help enterprises automate decision-making, improve compliance, and unlock operational efficiency.

Join our growing team of engineers, AI scientists, and innovators in building one of the most advanced agentic AI ecosystems.

Overview

As a Lead AI Engineer, you’ll be at the forefront of shaping Deep AI Lab’s agentic intelligence core — architecting scalable, compliant, and enterprise-ready AI platforms. You’ll lead design and development efforts across LLM orchestration, retrieval pipelines, vector intelligence, and agent collaboration frameworks, contributing directly to the innovation roadmap of our flagship platform.

Key Responsibilities

• Architect and implement LLM-driven agent frameworks with contextual memory, retrieval, reasoning and workflow automation capabilities.
• Research and develop the self-orchestration agentic layer for autonomously handling the custom workflows.  
• Lead development of knowledge-grounded AI components, combining RAG, agentic AI framework (LangGraph) and observability patterns. 
• Evaluate and integrate embedding/LLM models, vector/graph databases, and semantic retrieval systems, and agentic technologies.
• Mentor AI engineers and establish best practices throughout the SDLC pertaining to our knowledge-grounded, agentic AI platform.  
• Work closely with the MLOps team to operationalize scalable and secure AI pipelines.
• Continuously monitor emerging agent-led AI platforms, perform gap analyses, and design strategic innovations for our product roadmap.
• Ensure compliance, data privacy, and ethical AI governance across deployments.
• Collaborate with engineering, qa and product teams for achieving the individual and team’s objectives. 
• Prepare and maintain technical documentations pertaining to Platform’s AI ecosystem and pipelines.  

Candidate Requirements

• 5+ years of experience in AI/ML engineering, NLP systems, or applied research.
• Proficient in Python and LangGraph framework and deep understanding on Agentic AI protocols such as MCP & A2A.  
• Deep knowledge of LLMs, embeddings, retrieval-augmented generation (RAG), and multi-agent orchestration.
• Hands-on experience with vector DBs (Pinecone, Weaviate, Milvus, Amazon OpenSearch, PgVector, Chroma DB) and graph DBs (Neo4j, TigerGraph, ArangoDB). 
• Familiar with production AI deployment (Docker, Kubernetes, or serverless frameworks).
• Strong understanding of model evaluation, context engineering, prompt optimization, and system scaling.
• Hands-on experience in using any of the cloud providers (AWS, Azure and GCP).
• Exposure to enterprise AI security, explainability, and compliance frameworks.
• Bonus: Prior experience in designing and developing the multi-AI agentic ecosystem. 

What You Get

• Above market salary (USD based).
• Medical insurance.
• Learning and mentorship from senior AI experts. 
• Opportunity to lead AI innovation in collaboration with top global enterprises 
• Opportunities for global collaboration. 
• Participation in the Tech / AI conferences and  summits. 
• Autonomy to shape the evolution of our flagship agentic AI architecture.

If your skills and experiences align with our requirements and you are passionate about AI, please send your resume to hello@deepailab.com with the subject line of “Lead AI Engineer”. Only shortlisted will be contacted.