Avathon - Forward/Senior AI Engineer - Generative AI & LLMs (India)

Avathon - Forward/Senior AI Engineer - Generative AI & LLMs (India)

29 Sep
|
Hirist.tech
|
India

29 Sep

Hirist.tech

India

Note : If screened-in, you will be invited for initial rounds on 10th October 2026 (Saturday) in Bangalore.

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.

- 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.

About the Role :

As a Senior 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.

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.

You'll Have :

- Bachelor's or Master's degree in Computer Science,



Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
- Hands-on industry experience in AI Engineering, Machine Learning Engineering, Applied AI, or related roles.
- Strong experience building and deploying LLM/SLM-based applications in production environments.
- Solid expertise with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar.
- Robust understanding of transformer architectures, LLM/SLM 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.

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/SLM 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.
- Industry exposure in one or more of the following domains : Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy.

📌 Avathon - Forward/Senior AI Engineer - Generative AI & LLMs (India)
🏢 Hirist.tech
📍 India

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