About the Role
Senior AI Engineer - Generative AI & LLMs
At Avathon, we are building cutting-edge AI solutions that transform operations across asset-intensive industries such as Supply Chain, Logistics, Energy, Mining, Aerospace, and Industrial Manufacturing. As an AI Engineer, you will play a critical role in designing, developing, and deploying scalable AI systems with a strong focus on Generative AI, Large Language Models (LLMs), and production-grade machine learning applications.
This role is ideal for someone with strong engineering depth who can bridge research and production-building robust AI platforms, optimizing LLM workflows, and delivering high-impact solutions across forecasting, route optimization, anomaly detection, predictive maintenance, and intelligent automation.
With 3-5 years of hands-on industry experience, you are expected to bring expertise in AI system design, ML engineering, LLM deployment, and scalable software development within fast-paced startup environments.
You Will
- Design, build, and deploy production-grade AI/ML systems with strong emphasis on Generative AI and LLM-powered applications
- Develop and optimize end-to-end LLM pipelines including RAG architectures, fine-tuning, prompt orchestration, evaluation, and observability
- Build scalable backend services and APIs for AI applications using modern engineering best practices
- Implement and productionize transformer-based models and GenAI workflows for enterprise use cases
- Design vector search systems, embedding pipelines, and retrieval frameworks for knowledge-intensive applications
- Partner closely with Product, Engineering, and Business teams to translate operational challenges into scalable AI solutions
- Drive experimentation, benchmarking, model evaluation, and performance optimization with scientific rigor
- Improve inference efficiency, latency optimization, cost management, and reliability of deployed AI systems
- Establish guardrails, hallucination detection, monitoring, and responsible AI practices for production deployments
- Contribute to MLOps workflows including CI/CD, model lifecycle management, observability, and cloud deployment
- Stay current with the latest advancements in LLMs, agentic systems, foundation models, and applied AI engineering
You'll Have
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field
- 3-5 years of hands-on industry experience in AI Engineering, Machine Learning Engineering, Applied AI, or related roles
- Strong experience building and deploying LLM-based applications in production environments
- Solid expertise with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar
- Strong understanding of transformer architectures, LLM fine-tuning, prompt engineering, RAG systems, and vector databases
- Experience building scalable APIs and backend systems supporting AI workflows
- Familiarity with cloud platforms such as AWS, GCP, or Azure
- Strong software engineering fundamentals including system design, debugging, performance optimization, and production reliability
- Experience with containerization, deployment pipelines, and collaborative engineering environments
- Strong analytical thinking, ownership mindset, and ability to work in ambiguous, fast-moving startup environments
- Strong communication skills and ability to work cross-functionally with technical and business stakeholder
Preferred Qualifications
- Exposure to Retrieval-Augmented Generation (RAG), vector databases, or embedding-based search systems
- Familiarity with LLM observability and evaluation tools (e.g., Langfuse, LangSmith, Arize Phoenix, Weights & Biases)
- Hands-on experience with practical LLM deployment -- prompt versioning, cost/latency tracking, guardrails, or hallucination detection
- Exposure to LLM evaluation frameworks (e.g., RAGAS, DeepEval) or LLM-as-judge evaluation patterns
- Basic understanding of MLOps practices and model lifecycle management
- Experience working on applied AI projects in academic, internship, or startup settings
- Interest in industrial AI and asset-intensive environments
- Industry exposure in one or more of the following domains: Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy
Interview Process
As part of the interview process, you will be asked to complete a technical assessment.
Benefits & Perks
What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees -- we'd love to connect and share more!
- Evolving culture with the opportunity to drive new ideas and technology
- Stock Option Grants
- Medical Coverage and Parental Leave Plans
- 401k with Employer Match
- Monthly Technology Allowance
- Newly renovated office space located near Pleasanton, CA -- including fully stocked beverage and snack areas
Contract and temporary roles are not eligible for the above benefits.
Compensation
Pay Range:ย $110k - $130k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.
Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.