Senior AI Engineer - Product Engineering

The role

You will design, build, and deploy production-grade AI/ML systems with a focus on Generative AI and LLM-powered applications. You will develop LLM pipelines, build scalable backend services, and partner with product and business teams to solve operational challenges.

What you will do

• Design, build, and deploy production-grade AI/ML systems
• Develop and optimize end-to-end LLM pipelines including RAG architectures, fine-tuning, and prompt orchestration
• Build scalable backend services and APIs for AI applications
• Implement and productionize transformer-based models and GenAI workflows
• Design vector search systems, embedding pipelines, and retrieval frameworks
• Partner with Product, Engineering, and Business teams
• Drive experimentation, benchmarking, model evaluation, and performance optimization
• Improve inference efficiency, latency optimization, cost management, and reliability
• Establish guardrails, hallucination detection, monitoring, and responsible AI practices
• Contribute to MLOps workflows including CI/CD and cloud deployment

Required qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field
• 3–6 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

Nice to have

• 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

Before you apply

• You will be asked to complete a technical case study assessment
• Expect at least two-three rounds of Technical interviewing rounds and one onsite round

About the company

Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries accelerate the journey toward autonomous operations.