AI Lead $$$$ Offline

AI Lead — (Remote)

We are looking for a technically strong AI Lead to shape the future of AI across our organization. This role is ideal for someone with a solid hands-on engineering background (such as backend, infrastructure, or systems development) who has transitioned into AI and large model systems.

As an AI Lead, you will define and execute our AI strategy, architect scalable and secure systems, and guide a high-performing team of engineers. You’ll work with cutting-edge technologies such as vLLM, TensorRT-LLM, Hugging Face Transformers, and LangChain, and solve complex challenges in distributed training, inference optimization, and system scaling.
 

We strongly prefer candidates who have first built a strong foundation in software or systems engineering before moving into the AI stack.

About the Role:
We’re seeking a passionate, technically strong AI Lead to shape the future of AI across our
organization. In this high-impact role you’ll drive architecture, implementation, and adoption
of cutting-edge models, partnering closely with product and infrastructure teams to embed AI
at scale. You’ll own the AI roadmap, ship production-grade systems, and guide a talented
group of engineers and researchers.

Responsibilities:
- Lead the AI Vertical: Define and execute the technical vision and roadmap for AI across the company.
- Architect and Implement: Design scalable, secure, and high-performance AI systems; be hands-on with frameworks like vLLM, Hugging Face Transformers, LangChain, or/and similar MLOps stacks for training, fine-tuning, and inference.
- Collaborate with Product Teams: Partner with Product Managers to align AI innovations with business priorities and customer needs.
- Scale and Optimize: Solve complex performance and scalability challenges, especially around model serving, inference latency, distributed training, and memory optimization.
- Ensure Security: Identify and mitigate security risks unique to AI/ML systems, including prompt injection, model misuse, and data leakage.
- Mentor and Lead: Guide a team of engineers; promote best practices in AI system development, model evaluation, and MLOps.
- Stay Ahead of the Curve: Track the latest advances in LLMs, inference
optimization, vector databases, and agentic AI; turn emerging ideas into practical solutions for fast-moving, AI startups.

Requirements:
- Proven experience leading AI/ML teams and owning AI-driven product lines end to end.
- Strong hands-on expertise with LLM inference frameworks such as vLLM, TensorRT-LLM, TGI, or llama.cpp, and experience with model quantization, fine-tuning, and serving.
- Deep understanding of AI system design, distributed training, inference pipelines, model monitoring, and supporting multi-modal data pipelines for the end user.
- Strong proficiency in Generative AI, LLMs, multimodal AI for Agentic usage.
- Familiarity with performance tuning, latency reduction techniques, and memory optimization in large-scale AI applications.
- Awareness and experience handling security issues specific to AI systems.
- Demonstrated ability to partner with Product, DevOps, and Security teams to take models from prototype to production.
- Strong communication and leadership skills.

Nice to Have:
- Experience deploying LLMs in a multi-tenant SaaS environment.
- Familiarity with vector databases (e.g., FAISS, Weaviate, Qdrant, pg_
vector).
- Prior contributions to open-source AI frameworks or research publications in the field.
- Experience with GPU orchestration platforms and cost optimization techniques.
- Experience with on-device and efficient LLM inferencing methods