Role focuses on: Context Engineering, Memory and System
What You’ll Do
As a Founding AI Engineer, you will own the entire intelligence layer of this vision from scratch. You will drive the end-to-end implementation of a highly personalized AI assistant across multimodal signals, context engineering, memory, and actions, while shaping an AI architecture that fiercely protects user privacy and data boundaries.
- Multimodal Context Understanding: Build AI systems that understand real-world user context from multimodal inputs
- Memory & Personalization Infrastructure: Design context and memory systems that support deep user insights and personalization over time.
- Retrieval & Reasoning: Develop systems that reason over the right context at the right moment to help the product assist users timely and usefully.
- Productization of AI Pipeline: Build and own the pipelines, model workflows, APIs, storage, evaluation, monitoring, and privacy-first data handling behind all of it.
- Cross-function Collaboration: Work closely with product, design, and engineering to turn ambiguous human needs into robust AI capabilities.
What We’re Looking For
- Bachelor’s degree or above in CS or a related field
- At least 3 years of full-time work experience in related field
- At least 2 year of Gen AI experience building and shipping applied generative AI systems end to end
- Hands-on experience building and shipping AI systems with LLMs, VLMs, or multimodal models, including the ability to run, adapt, and evaluate open-source models such as DeepSeek, Qwen, Llama, or similar.
- Deep understanding of context engineering — RAG, memory systems, embeddings, retrieval/ranking, MCP servers, agent frameworks, or other ways of making models reason over context they did not see in pretraining.
- Strong Python and backend/systems engineering ability. You can stand up pipelines yourself and take ambiguous ideas all the way to working systems.
- Action-driven: when you hear a vague idea, your hands start moving.
- Absolute ownership in a fast-paced and high-intensity start-up environment
- Clarity of thought, excellent communication
Bonus
- Experience with Docker, Kubernetes, or major cloud platforms such as AWS, GCP, or Azure.
- Early-stage start up experience
Compensation and benefits
- Competitive base salary
- Meaningful early-stage equity
- Comprehensive health, dental, and vision coverage
- Immigration support: H1-B and green card sponsorship available for qualified candidates
Pay: $150,000.00 - $250,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Flexible schedule
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Referral program
- Relocation assistance
- Retirement plan
- Vision insurance
Work Location: In person
