Principal Engineer

About Us

At Kizen, we’re engineering a more humane future where AI drives universal healthcare, more impactful work, world-class education, exceptional customer experiences, and — overall — a more fulfilling human experience.

Kizen is on a mission to give every team member an AI Assistant - turning every company into an AI-company, every worker into an AI-Enhanced Worker, and every Process into an AI-optimized, continuously improving process. Kizen is the first GenAI enterprise application builder. Businesses of any size, within any industry can build AI assistants for complex jobs across healthcare, finance, and HR and modern enterprise applications - like CRMs, Workflow Automation, Real Time Dashboards, and Secure Portals in minutes and perfect them in an afternoon. Kizen helps teams systematically improve processes and business outcomes with data-driven insights and powerful automation with access to all the latest AI models.

About the Role

Shape the Future of AI at Kizen

Are you ready to push the boundaries of what's possible with AI and backend systems? At Kizen, we're engineering intelligent systems that combine cutting-edge AI with robust backend architecture to revolutionize healthcare, redefine work-life balance, transform education, and elevate customer experiences. Our mission is to create technology that doesn't just work – it transforms how businesses operate.

As we rapidly expand, we're seeking exceptional engineers who excel in both AI development and backend systems. This is your opportunity to be part of something transformative – to architect and build systems that set new benchmarks for what technology can achieve across industries.

At Kizen, you'll join a brilliant, fun team tackling challenges that matter. We offer:

The opportunity to work on groundbreaking AI technologies with real-world impact

A startup culture that values innovation, ownership, and rapid iteration

Regular opportunities to present your technical solutions to company leadership

A supportive environment for professional growth and learning

We're looking for a Principal AI Engineer to provide strategic feedback and direction for our engineering team as we bring our next-generation platform to the world. In this position, you'll architect, plan, and build sophisticated AI systems with collaborators seamlessly integrating with our backend infrastructure, focusing on generative AI, retrieval-augmented generation (RAG), and multi-agent architectures.

Key Responsibilities

Lead the design and implementation of production-ready RAG systems that integrate seamlessly with our backend infrastructure using Django, Kafka, PostgreSQL, and Clickhouse

Architect multi-agent AI systems that operate effectively within our platform's constraints and understand business value implications.

Drive product strategy by providing accurate work estimations and technical roadmaps with minimal supervision.

Design and implement sophisticated vector search solutions, including graph-based RAG systems

Architect and build highly scalable LLM-powered systems that can handle enterprise-level workloads

Lead LLM fine-tuning initiatives to customize models for specific business domains and use cases

Design and implement user feedback systems to collect, analyze, and incorporate insights for continuous improvement

Optimize LLM performance, cost, and reliability in production environments

Establish MLOps best practices using platforms like Langfuse or LiteLLM to ensure robust model monitoring and evaluation

Mentor and develop junior engineers in AI/ML best practices

Collaborate with cross-functional teams to translate business requirements into technical solutions

Lead system architecture decisions and technical direction for AI initiatives

Evaluate emerging AI technologies for potential adoption

Experience

Required Qualifications

Education and Experience

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field

8+ years of backend engineering experience with Django, Kafka, and PostgreSQL

4+ years of hands-on experience building and deploying machine learning systems

Proven track record of implementing production RAG systems at scale

Strong experience in product management, including work estimation and roadmap planning

Experience building solutions at scale with large enterprise data in healthcare, finance, or banking sectors.

Technical Expertise

Expert-level Python development skills with Django experience

Deep understanding of distributed systems and message queuing using message broker systems (e.g., Kafka)

Advanced PostgreSQL knowledge, including optimization for AI workloads

Experience building and optimizing retrieval-augmented generation (RAG) systems

Experience architecting and implementing multi-agent AI systems

Knowledge of deep learning frameworks (PyTorch or TensorFlow) and NLP, particularly transformer architectures

Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes)

Experience building solutions using pre-trained LLMs (OpenAI, Claude, Llama, etc.)

Strong background in MLOps practices and tools, including platforms like Langfuse or LiteLLM

Proficiency in writing clean, well-documented code and troubleshooting complex issues

Experience in testing and validating products and communicating results with stakeholders

ML/AI Experience

Experience applying graph algorithms to machine learning problems

Strong experience with modern NLP techniques and transformer architectures

Knowledge of evaluation metrics for NLP system performance

Solid foundation in probability theory and statistical inference

Experience with statistical modeling and hypothesis testing

Understanding of sampling methods and experimental design

LLM Systems Expertise

Proven experience designing and implementing scalable LLM-powered systems in production environments

Deep understanding of LLM orchestration and optimization techniques for high-throughput applications

Experience with prompt engineering, fine-tuning, and context window management for optimal LLM performance

Demonstrated expertise in LLM fine-tuning methodologies, including RLHF, PEFT, and LoRA techniques

Experience building data collection pipelines for LLM training and fine-tuning

Knowledge of efficient usage strategies, cost optimization for LLM API consumption, and performance optimization of large-scale deployments.

Experience implementing LLM caching mechanisms and vector store optimizations

Expertise in designing fault-tolerant LLM architectures with appropriate fallback mechanisms

Understanding of techniques to reduce latency in LLM-powered applications

Knowledge of strategies for handling data privacy and security in LLM applications

User Feedback and System Improvement

Knowledge of model monitoring and evaluation techniques

Experience designing and implementing robust user feedback collection systems for AI applications

Knowledge of feedback aggregation and analysis techniques to identify patterns and improvement areas

Experience building systems that leverage user feedback for continuous LLM improvement

Understanding of human-in-the-loop approaches for refining AI system outputs

Experience with A/B testing frameworks to evaluate AI system changes

Ability to translate user feedback into actionable model improvements

Experience implementing evaluation frameworks to measure AI system quality and performance

Professional Skills

Demonstrated ability to lead technical initiatives and architectural decisions

Experience managing technical product roadmaps and providing accurate work estimations

Strong problem-solving skills and ability to work independently on complex projects

Strategic thinking ability to balance immediate solutions with long-term scalability

Excellent collaboration skills when working with cross-functional teams

Excellent written and verbal communication skills in English

Driven, self-motivated, adaptable, empathetic, energetic, and detail-oriented

Preferred Qualifications

Experience with graph-based RAG systems

Contributions to open-source projects in backend or AI domains

Experience with streaming data processing at scale

Deep interest in emerging AI technologies and their practical applications

Strong mentoring capabilities to guide and develop team members

Ability to work in our Los Angeles or Austin office

Why Kizen

We’re a fast-growing company that values innovation, growth, and continuous improvement. By joining Kizen, you’ll play a pivotal role in shaping the future of the company while enjoying a supportive, dynamic, and collaborative workplace. You’ll have opportunities for professional development, impact, and career advancement.

What We Offer

Hybrid Work Model

Career Growth Opportunities

Engaging Work Culture

Top-Tier Compensation

Equity Package

Healthcare Coverage

Professional Development Stipends

PTO

Kizen is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics. At Kizen, we fully comply with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals.

The base salary range for this position is $200,000-$250,000. However, base pay offered may vary depending on job-related knowledge, skills, and experience. In addition to base salary, we also offer generous equity and benefits packages.

If you’re excited about creating impact experiences and contributing to a fast-paced, people-focused team, we’d love to meet you!

OTE - $250-$300K