Senior AI Engineer (Principal-Level Scope)

About the Company

We are building an AI system focused on domain-specific scientific problem-solving, particularly in areas such as gene pathways and experimental analysis.

Our goal is to go beyond general-purpose LLMs by developing agentic AI systems that can understand experimental context, integrate structured and unstructured scientific knowledge, and assist in reasoning, diagnosis, and decision-making.

Position: Senior AI Engineer

We are looking for a Senior AI Engineer with a strong engineering mindset to lead the design, development, and deployment of production-grade AI systems.

This role goes beyond traditional model development, you will be involved in the full AI system, from model decisions to infrastructure, and from experimentation to scalable deployment.

You will play a key role in building agentic AI systems, integrating LLMs with tools, data, and real-world workflows to solve complex domain-specific problems.

Key Responsibilities

1. Infrastructure & Production Engineering

* Design and manage AI infrastructure and related pipelines

* Build scalable systems including inference services, data pipelines, and evaluation pipelines

* Lead or contribute to DevOps practices, cloud deployment (e.g., AWS/GCP), and system monitoring

* Ensure reliability, scalability, and performance in production environments

2. End-to-End AI System Ownership

* Design, build, and maintain production-ready AI systems

* Participate in the full lifecycle: prototyping → evaluation → deployment → scaling → monitoring

* Ensure maintainability and robustness in real-world usage

3. Agentic AI System Design

* Architect and implement multi-agent workflows

* Design prompt strategies, tool usage, memory systems, and planning mechanisms

* Develop robust approaches for context management, long-horizon reasoning, and tool orchestration

4. Model Strategy & System Optimization

* Select appropriate models and approaches based on engineering constraints (performance, latency, cost)

* Contribute to fine-tuning or adapting open-source models when needed

* Build stable evaluation and iteration frameworks to continuously improve system performance

5. Cross-Functional Collaboration

* Work closely with product, research, and deployment teams

* Mentor junior engineers and contribute to technical direction

* Translate ambiguous requirements into robust engineering solutions

Requirements

Core Engineering Skills

* 4 years of experience in software engineering or AI engineering

* Proven experience building and shipping production systems

* Proficiency in Python and modern backend frameworks

* Strong foundation in system design, scalability, and reliability

AI / LLM Experience

* Hands-on experience with LLMs and agent-based systems

* Understanding of common model enhancement approaches (e.g., retrieval, fine-tuning)

* Experience in model optimization or real-world deployment is preferred

System Thinking

* Ability to bridge model capabilities with system design

* Strong intuition for trade-offs between cost, latency, and quality

* Ability to decide when to rely on engineering solutions vs. model improvements

Good to Have

* Experience with multi-agent frameworks (e.g., LangGraph, AutoGen)

* Experience in scientific domains

* Familiarity with vector databases or retrieval systems

* Experience with distributed systems or large-scale data pipelines

What We’re Looking For

* Someone who thinks like an engineer first, not just a model user

* Comfortable owning complex, ambiguous, high-impact problems

* Able to move between high-level system design and low-level implementation details