AI Engineer

Who We Are & Why Join Us

Avathonis the leading Industrial AI autonomy platform helping customers across heavy industries -- energy mining manufacturing aerospace defense and logistics -- accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems bringing together time series structured unstructured and machine vision data to power AI-driven applications in asset performance management supply chain intelligence visual AI and global trade management. With capabilities spanning digital twins normal behavior modeling natural language processing and computer vision Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale.

Cutting-Edge AI Innovation-- Join a team at the forefront of AI developing groundbreaking solutions that shape the future.High-Growth Environment-- Thrive in a fast-scaling startup where agility collaboration and rapid professional growth are the norm.Meaningful Impact-- Work on AI-driven projects that drive real change across industries and improve lives.

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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 productionbuilding robust AI platforms optimizing LLM workflows and delivering high-impact solutions across forecasting route optimization anomaly detection predictive maintenance and intelligent automation.

With 35 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

Youll Have

• Bachelors or Masters degree in Computer Science Artificial Intelligence Machine Learning Data Science or a related technical field
• 35 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 -- wed 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:$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.