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Generative AI Engineer – LLM & Enterprise Knowledge Systems
Generative AI Engineer – LLM & Enterprise Knowledge Systems
aurusai's logo

Generative AI Engineer – LLM & Enterprise Knowledge Systems

Uday Ayyagari's profile picture
Posted by Uday Ayyagari
4 - 10 yrs
₹10000L - ₹1500000L / yr
Remote only
Skills
Generative AI
Retrieval Augmented Generation (RAG)
Prompt engineering
Natural Language Processing (NLP)
OpenAI
Large Language Models (LLM) tuning
Llama
Cloudera
PEFT (Parameter-Efficient Fine-Tuning)
Model-View-View-Model (MVVM)

About the Role:

We are looking for an experienced and imaginative Generative AI Architect & Engineer to lead, design, and build cutting-edge solutions using Large Language Models (LLMs) such as OpenAI’s GPT-4/5, Google Gemini, Meta’s LLaMA, and Anthropic Claude. You will spearhead the development of a corporate-wide GenAI platform that harnesses proprietary enterprise knowledge and empowers sales, operations, and other departments with instant, contextual insights, guidance, and automation.

As the GenAI leader, you will be responsible for building scalable pipelines, integrating enterprise content repositories, fine-tuning or adapting foundational models, and creating secure and intuitive access patterns for business teams. You are passionate about creating highly usable solutions that solve real-world problems, and are fluent across architecture, implementation, and MLOps best practices.


Key Responsibilities:

  • Architect and implement an end-to-end GenAI solution leveraging LLMs to serve as a contextual assistant across multiple business units.
  • Develop pipelines to ingest, clean, and index enterprise knowledge (documents, wikis, CRM, chat transcripts, etc.) using RAG (Retrieval-Augmented Generation) patterns and vector databases.
  • Lead fine-tuning, prompt engineering, and evaluation of LLMs, adapting open-source or commercial models to enterprise needs.
  • Design a secure, scalable, API-first microservice platform, including middleware and access control, integrated into corporate systems.
  • Work closely with sales, operations, and customer support teams to gather use cases and translate them into impactful GenAI features.
  • Drive experimentation and benchmarking to evaluate various open and closed LLMs (OpenAI, Claude, Gemini, LLaMA, Mistral, etc.) for best performance and cost-efficiency.
  • Collaborate with DevOps teams to enable MLOps workflows, CI/CD pipelines, versioning, and A/B testing for AI models.
  • Contribute to technical documentation, best practices, and internal knowledge sharing.


Key Qualifications:

  • 4–5+ years of hands-on experience in AI/ML product development or applied research.
  • Demonstrated experience working with LLMs (OpenAI, LLaMA, Claude, Gemini, Mistral, etc.) and RAG pipelines, including vector search (FAISS, Weaviate, Pinecone, Chroma, etc.).
  • Strong Python skills and experience with frameworks such as LangChain, LlamaIndex, Transformers, Ray, HuggingFace, or equivalent.
  • Deep understanding of NLP, model fine-tuning, embeddings, tokenization, and content ingestion pipelines.
  • Exposure to enterprise content systems (e.g., SharePoint, Confluence, Salesforce, internal wikis, etc.) and integrating with them securely.
  • Solid foundation in software architecture, microservices, API design, and cloud deployments (Azure, AWS, or GCP).
  • Experience with security, RBAC, and compliance practices in enterprise-grade solutions.
  • Ability to lead projects independently and mentor junior engineers or data scientists.


How to Apply:

Submit your resume and a short technical project summary or portfolio (GitHub, Hugging Face, blog posts)

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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About aurusai

Founded :
2018
Type :
Product
Size :
0-20
Stage :
Raised funding

About

aurus.ai is a category-defining AI-as-a-Service (AIaaS) platform with a mission to commoditize enterprise-grade AI, making powerful LLM-based capabilities accessible, relevant, and affordable for businesses of all sizes. From automating complex financial, supply chain or insurance document workflows to enabling real-time decisioning from unstructured data, our platform turns friction into functionality. We deploy a modular, functional architecture that empowers SMBs and enterprises alike to plug into the future of intelligent automation—quickly, securely, and at scale.

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Candid answers by the company

What does the company do?
What is the location preference of jobs?
How many SaaS products have you led (any capacity), and shipped .

Aurus.ai is an enterprise AI platform that helps businesses automate document-heavy workflows, run predictive risk assessments, and interact with data through natural language. Its products include DoKrunch (document intelligence and automation), RiskLens (risk scoring and predictive modeling), and Cortus (a conversational interface to “speak with your data”). Aurus.ai serves SMBs and enterprises across sectors like finance, insurance, and supply chain, offering faster processing, higher accuracy, and better ROI through AI-driven automation and decision support.

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Press:  https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/

Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/

  • 2019 Edge Computing Company of the Year – Compass Intelligence
  • 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
  • 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
  • 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
  • 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
  • 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
  • 2018 The 10 Most Innovative AI Solution Providers – Insights Success
  • 2018 The AI 100 – CB Insights
  • 2017 Cool Vendor in IoT Edge Computing – Gartner
  • 2017 20 Most Promising AI Service Providers – CIO Review

Our Series A round was for $15 million.  Our Series B round was for $30 million October 2017.  Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.

About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9.  We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects.  About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.

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  • Give or receive mentoring as part of the collaborative process
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  • Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning

 

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I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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