Senior AI Engineer – Multimodal Agents & Systems

ALETHIA AI Labs is seeking a Senior AI Engineer passionate about integrating language, vision, and audio models into seamless, real-time agentic experiences. As a leader in the Agentic AI movement, ALETHIA AI collaborates with industry pioneers like Solana Mobile, AWS, and OpenSea to develop decentralized AI foundations. The company has pioneered intelligent NFTs (iNFTs) and advanced on-chain AI agents for mobile platforms. In this full-time role, you will design and deploy production-ready AI architectures that unify large language models (LLMs), speech, and computer vision with tooling, memory, and blockchain components. You will work closely with product and platform teams to transform prototypes into scalable, reliable systems powering interactive AI agents across mobile, web, and decentralized environments.

Key Responsibilities
- Design and implement multimodal AI components that integrate LLMs, speech, and vision models within agent workflows.
- Collaborate with product and research teams to translate user-facing experiences into detailed model, API, and data specifications.
- Prototype, benchmark, and optimize AI pipelines for latency, throughput, and reliability in real-time or near-real-time applications.
- Partner with backend and infrastructure teams to package models as services, deploy them on GPU environments, and manage scaling and cost efficiency.
- Define and execute evaluation strategies for end-to-end agent behavior, including offline metrics and live experiments.
- Contribute to internal tooling, libraries, and best practices to accelerate AI development across the organization.
- Stay informed on emerging model architectures, APIs, and open-source projects to guide build-versus-buy decisions.

Required Qualifications
- Minimum of 5 years’ experience in machine learning or applied AI engineering, including delivering production systems.
- Strong proficiency in Python and hands-on experience with at least one major deep learning framework such as PyTorch.
- Practical experience integrating LLMs into applications, including prompt engineering, context management, and API orchestration.
- Experience deploying LLM-based or multimodal AI models on edge or resource-constrained devices, with a focus on latency and reliability.
- Hands-on work with multimodal LLMs combining text with at least one other modality (speech, vision, or video) in production or research environments.
- Familiarity with cloud infrastructure, containerization, and basic MLOps practices for model deployment and monitoring.
- Ability to evaluate trade-offs between model size, latency, cost, and quality in real-world product settings.
- Excellent communication skills and ability to collaborate effectively with cross-functional teams in a fast-paced environment.

Preferred Qualifications and Benefits
- Experience building agentic systems that coordinate multiple tools, APIs, or models to accomplish complex tasks.
- Background in personalization, recommendation systems, or reinforcement learning aimed at optimizing long-term agent behavior.
- Knowledge of WebRTC, streaming, or other real-time technologies used in interactive AI experiences.
- Familiarity with Web3 concepts such as wallets, digital signatures, or smart contract interactions is a plus.
- Competitive salary with tax deductions ranging from 0.25% to 1%, along with role-aligned incentives and opportunities for professional growth.

If you are excited to contribute to a pioneering community at the intersection of AI and Web3 innovation, this is an excellent opportunity to join a forward-thinking team shaping the future of decentralized AI agents.