The Role
Design, develop, and deploy production AI systems (RAG, LLM agents, document intelligence, conversational AI). Build robust pipelines, optimize prompts and models, manage data and ETL, deploy on cloud, monitor and iterate, and collaborate with product and client teams to deliver reliable, scalable AI solutions.
Summary Generated by Built In
AI EngineerFull-Time - San Diego, CA - USA
About Cadre AI
The Role
What You’ll Do
Build and Ship Production AI Systems
Optimize Models and Prompts
Own Data and Infrastructure
Collaborate and Contribute
Who You Are
What Sets You Apart
Why Cadre AI
About Cadre AI
Cadre AI is an AI strategy and integration firm that builds production AI systems for B2B companies in private equity, wholesale lending, real estate, and SaaS. We don’t build decks about what AI could do. We ship systems that move revenue, compress costs, and automate the work that used to take entire teams.
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.
- 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
- 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
- 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
- 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.
Cadre AI is building the future of how companies adopt and operate AI. We believe the best AI systems come from engineers who understand both the technology and the business it serves. If that’s how you think, we want to talk.
CompensationThe base pay range for this role is $70,000 – $85,000 per year.
Skills Required
- 5+ years of experience as an AI/ML Engineer or closely related role focused on shipping production systems
- Hands-on expertise with modern LLMs (OpenAI GPT-4, Anthropic Claude, Google Gemini, open-source models like Llama)
- Strong experience building RAG systems, agent frameworks, and LLM chains at scale
- Proficient in Python
- Experience with PyTorch
- Solid understanding of machine learning algorithms, deep learning techniques, and natural language processing
- Experience evaluating ML models and LLMs with appropriate metrics, testing, and validation
- SQL proficiency (PostgreSQL)
- Data warehouse experience (Snowflake)
- Experience deploying AI models on cloud platforms (AWS, GCP, or Azure)
- Experience with big data technologies (Hadoop or Spark)
- Open-source contributions or active participation in AI research communities
- Domain knowledge in financial services, real estate, lending, or B2B SaaS
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- Strong analytical and problem-solving skills with clear communication to non-technical stakeholders
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The Company
What We Do
Cadre is an AI strategy and integration firm focused on helping organizations unlock the power of AI to drive measurable business results that grow revenue, increase EBITDA, and unlock scalability. We implement best-in-class AI tools and technologies to AI-Enable your business and create a lasting competitive advantage. Our combination of entrepreneurial experience, strong operational understanding and technical AI expertise enables us to help our clients integrate cutting-edge AI technologies to drive efficiency, productivity, and growth. As a team we take an “ownership mindset” to our clients business, asking ourselves “what moves would I make if this was my business” and are committed to transforming your company into a “future-proof” organizations by leveraging the power of AI to achieve operational excellence and enhanced profitability and putting you ahead of your competitors and industry.
