AI Engineer

Go Cadre • San Diego, CA

5d

About The Position

The AI Engineer at Cadre AI is a core builder on our delivery teams. You design, develop, and ship the AI systems that power our clients’ most critical workflows—RAG pipelines, LLM agents, document intelligence, conversational AI, and predictive models. This is not a research role. You work on production systems used by real businesses, and you are accountable for how they perform. You’ll work closely with Forward Deployed Engineers, AI Strategists, and client stakeholders to turn business problems into scalable, reliable AI solutions. You bring strong ML fundamentals, hands-on LLM expertise, and the engineering discipline to take a model from experiment to production without cutting corners.

Requirements

• 5+ years of experience as an AI/ML Engineer or in a closely related role, with a focus on shipping production systems—not proofs-of-concept
• Hands-on expertise with modern LLMs including OpenAI GPT-4, Anthropic Claude, Google Gemini, and open-source models like Llama
• Strong experience building RAG systems, agent frameworks, and LLM chains that work reliably at scale
• Proficient in Python and experienced with ML frameworks including PyTorch
• Solid understanding of machine learning algorithms, deep learning techniques, and natural language processing
• Experienced evaluating ML models and LLMs using appropriate metrics and methodologies—you know the difference between a good demo and a reliable system
• SQL proficiency (PostgreSQL) and data warehouse experience (Snowflake preferred)
• Strong analytical and problem-solving skills with the ability to work across disciplines and communicate clearly with non-technical stakeholders

Nice To Haves

• You have deployed AI models on cloud platforms (AWS, GCP, or Azure) and know what production readiness actually requires
• Open-source contributions in AI projects or active participation in AI research communities—you build in public and share what you learn
• Experience with big data technologies like Hadoop or Spark
• Domain knowledge in financial services, real estate, lending, or B2B SaaS—you understand the business context behind the systems you build
• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Responsibilities

• Design and implement machine learning models and AI pipelines for OCR, retrieval-augmented generation (RAG), conversational agents, document intelligence, and content generation
• Architect and deploy LLM-powered systems using OpenAI GPT-4, Anthropic Claude, Google Gemini, and open-source models including Llama
• Build robust agent frameworks, LLM chains, and orchestration layers that hold up in production under real-world conditions
• Deploy AI models into production environments and own their ongoing performance—monitoring, debugging, and iterating as needed
• Develop and optimize prompts for LLMs to improve output quality and align model behavior with specific business objectives
• Evaluate and fine-tune ML models and LLMs using rigorous testing, validation, and performance benchmarking methodologies
• Build evaluation frameworks and regression suites that prove your systems work—and catch when they don’t
• Apply the right technique for the problem: prompt engineering, RAG, fine-tuning, or classical ML based on the actual constraints of data, latency, and budget
• Collect, preprocess, and manage large datasets to support AI model training and deployment
• Design and enforce data quality rules, ETL pipelines, and secure cloud deployments across AWS, GCP, and Azure
• Work with SQL (PostgreSQL) and data warehouse tooling (Snowflake preferred) to support model pipelines and analytics
• Ensure clean data pipelines, strong governance, and actionable outputs across every engagement
• Work closely with Forward Deployed Engineers, AI Strategists, and product teams to integrate AI models into client-facing products and services
• Stay current on advancements in generative AI, LLMs, and ML frameworks—bringing new tools and techniques to the team when they’re actually worth using
• Contribute to Cadre’s internal AI frameworks, prompt libraries, and reusable components that accelerate delivery across pods
• Mentor junior engineers through design reviews, pair programming, and hands-on coaching

Benefits

• Real ownership. You build the systems, ship them, and see the impact directly. No writing tickets for someone else to close.
• Variety and velocity. Every engagement is a different industry, a different problem, and a new chance to build something that matters. You won’t get bored.
• AI-native culture. We don’t just build AI for clients. We use it to run our own operations. You’ll work with people who are as obsessed with the tools as you are.
• Access to the frontier. Through partnerships with Anthropic, OpenAI, and YC, you’ll be among the first to experiment with new models and capabilities.
• Upside. We’re bootstrapped, profitable, and growing fast. Early team members share in the success they help create.
• No bureaucracy. Small pods. Clear accountability. The best idea wins, regardless of who says it.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree