AI Engineer

Who We Are & Why Join Us

Avathon is 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 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 product ionize 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, Tensor Flow, Hugging Face, Lang Chain, Llama Index, 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, Lang Smith, Arize Phoenix, Weights & Biases)
• Hands-on experience with practical LLM deployment -- prompt versioning, cost/latency tracking, guardrails, or…