Generative AI Engineer – LLM & Enterprise Knowledge Systems

Generative AI Engineer – LLM & Enterprise Knowledge Systems at aurusai · Remote only · 4 - 10 years · ₹10000L - ₹1500000L / yr · Raised funding · Remote only · Posted 10 May 2025

Generative AI Engineer – LLM & Enterprise Knowledge Systems

at aurusai

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)

About the Role:

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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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.

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.

Company social profiles

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Generative AI (GenAI)

Python

Large Language Models (LLM)

+7 more

We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.

Key Responsibilities

Develop and enhance Generative AI applications using LLMs and AI frameworks.
Build and optimize RAG pipelines, vector search, and AI-powered workflows.
Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
Develop REST APIs and integrate AI capabilities into enterprise applications.
Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
Ensure code quality through testing, debugging, documentation, and code reviews.
Follow Responsible AI, security, and data governance practices.

Required Technical Skills

Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
Experience with PyTorch, TensorFlow, or Keras.
Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
Understanding of AI governance, data privacy, and Responsible AI principles.

Preferred Skills

Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
Knowledge of multimodal AI applications.

Qualifications

Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
5 years of software development experience, including AI/ML or Generative AI projects.
Experience building and deploying production-grade AI solutions.

Assessment Focus Areas

Candidates will be evaluated on:

Python coding and problem-solving
Data Structures & Algorithms
LLMs, RAG, and Agentic AI concepts
API development and system design
Cloud deployment and AI solution architecture

Key Responsibilities

Develop and enhance Generative AI applications using LLMs and AI frameworks.
Build and optimize RAG pipelines, vector search, and AI-powered workflows.
Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
Develop REST APIs and integrate AI capabilities into enterprise applications.
Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
Ensure code quality through testing, debugging, documentation, and code reviews.
Follow Responsible AI, security, and data governance practices.

Required Technical Skills

Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
Experience with PyTorch, TensorFlow, or Keras.
Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
Understanding of AI governance, data privacy, and Responsible AI principles.

Preferred Skills

Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
Knowledge of multimodal AI applications.

Qualifications

Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
5 years of software development experience, including AI/ML or Generative AI projects.
Experience building and deploying production-grade AI solutions.

Assessment Focus Areas

Candidates will be evaluated on:

Python coding and problem-solving
Data Structures & Algorithms
LLMs, RAG, and Agentic AI concepts
API development and system design
Cloud deployment and AI solution architecture

Python Gen AI Engineer

at VY SYSTEMS PRIVATE LIMITED

Posted by Indira N

Bengaluru (Bangalore)

4 - 6 yrs

₹1L - ₹15L / yr

Python

Generative AI (GenAI)

Agentic AI

Job Title: Python + GenAI Developer

Experience: 4–6 Years

Location: Bangalore / Hyderabad (as applicable)

Job Description:

We are looking for a skilled Python + Generative AI Developer with hands-on experience in Python development, LLM integration, and building AI-powered applications.

Key Responsibilities:

Develop backend applications and REST APIs using Python.
Build and integrate Generative AI solutions using LLMs.
Work with frameworks such as LangChain or LangGraph.
Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.
Integrate OpenAI or other LLM APIs into applications.
Collaborate with teams to develop, test, and deploy AI-powered solutions.
Work with cloud platforms such as AWS, Azure, or GCP.

Required Skills:

4–6 years of Python development experience.
Hands-on experience with Generative AI and LLMs.
Experience with LangChain or LangGraph.
Knowledge of RAG and vector databases.
Experience developing REST APIs using FastAPI or Flask.
Understanding of prompt engineering and LLM integration.
Familiarity with Git and cloud platforms.

Preferred Skills:

Experience with Agentic AI and AI agents.
Knowledge of embeddings and semantic search.
Experience with Docker and CI/CD.

Job Title: Python + GenAI Developer

Experience: 4–6 Years

Location: Bangalore / Hyderabad (as applicable)

Job Description:

We are looking for a skilled Python + Generative AI Developer with hands-on experience in Python development, LLM integration, and building AI-powered applications.

Key Responsibilities:

Develop backend applications and REST APIs using Python.
Build and integrate Generative AI solutions using LLMs.
Work with frameworks such as LangChain or LangGraph.
Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.
Integrate OpenAI or other LLM APIs into applications.
Collaborate with teams to develop, test, and deploy AI-powered solutions.
Work with cloud platforms such as AWS, Azure, or GCP.

Required Skills:

4–6 years of Python development experience.
Hands-on experience with Generative AI and LLMs.
Experience with LangChain or LangGraph.
Knowledge of RAG and vector databases.
Experience developing REST APIs using FastAPI or Flask.
Understanding of prompt engineering and LLM integration.
Familiarity with Git and cloud platforms.

Preferred Skills:

Experience with Agentic AI and AI agents.
Knowledge of embeddings and semantic search.
Experience with Docker and CI/CD.

Python GenAI

at VY SYSTEMS PRIVATE LIMITED

Posted by JAMSHIDA KATHUN

Hyderabad

8.5 - 20 yrs

₹15L - ₹20L / yr

Python

Generative AI

Large Language Models (LLM)

LangChain

LangGraph

+5 more

🚀 Hiring: Python GenAI / Agentic AI Engineer

📍 Location: Hyderabad

💼 Experience: 7+ Years

🤖 GenAI / Agentic AI: 2+ Years

Mandatory Skills:

• Strong Python development experience

• Generative AI / Agentic AI

• LLMs & Prompt Engineering

• LangChain / LangGraph

• RAG & Vector Databases

• AI Agents / Multi-Agent Systems

• FastAPI / REST APIs

• LLM Integration

• Microservices & API Architecture

• Git & CI/CD

Looking for candidates with strong hands-on experience in building GenAI/Agentic AI solutions using Python, LLMs, RAG, and AI Agent frameworks.

🚀 Hiring: Python GenAI / Agentic AI Engineer

📍 Location: Hyderabad

💼 Experience: 7+ Years

🤖 GenAI / Agentic AI: 2+ Years

Mandatory Skills:

• Strong Python development experience

• Generative AI / Agentic AI

• LLMs & Prompt Engineering

• LangChain / LangGraph

• RAG & Vector Databases

• AI Agents / Multi-Agent Systems

• FastAPI / REST APIs

• LLM Integration

• Microservices & API Architecture

• Git & CI/CD

Looking for candidates with strong hands-on experience in building GenAI/Agentic AI solutions using Python, LLMs, RAG, and AI Agent frameworks.

GenAI Engineer

at KDK Software

Posted by Priyanka Khandelwal

Jaipur

3 - 8 yrs

₹10L - ₹12L / yr

Generative AI (GenAI)

Large Language Models (LLM)

Retrieval Augmented Generation (RAG)

Job Description – AI Engineer (End-to-End Development & Deployment)

Role Summary

We are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.

Key Responsibilities

● Design, build, and deploy Generative/Agentic AI solutions.

● Develop applications using LLMs, RAG, AI agents, and vector databases.

● Build scalable APIs and integrate AI solutions with enterprise applications.

● Implement CI/CD pipelines, containerization, and MLOps best practices.

● Monitor, optimize, and maintain production AI systems.

● Collaborate with cross-functional teams to deliver business-driven AI solutions.

Required Skills

● Strong programming skills in Python.

● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems

● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI

● Experience with LLMs, RAG, GenAI, AgenticAI Agents

● Hands-on experience with FastAPI, and REST APIs.

● Knowledge of Docker, Kubernetes, Git, CI/CD.

● Experience with AWS, Azure, or GCP.

● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.

Job Description – AI Engineer (End-to-End Development & Deployment)

Role Summary

Key Responsibilities

● Design, build, and deploy Generative/Agentic AI solutions.

● Develop applications using LLMs, RAG, AI agents, and vector databases.

● Build scalable APIs and integrate AI solutions with enterprise applications.

● Implement CI/CD pipelines, containerization, and MLOps best practices.

● Monitor, optimize, and maintain production AI systems.

● Collaborate with cross-functional teams to deliver business-driven AI solutions.

Required Skills

● Strong programming skills in Python.

● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems

● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI

● Experience with LLMs, RAG, GenAI, AgenticAI Agents

● Hands-on experience with FastAPI, and REST APIs.

● Knowledge of Docker, Kubernetes, Git, CI/CD.

● Experience with AWS, Azure, or GCP.

● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.

AI Engineer

at Treosoft IT

Posted by Anish N

Bengaluru (Bangalore)

3 - 5 yrs

₹10L - ₹20L / yr

Python

Generative AI

Agentic AI

LangChain

LlamaIndex

+3 more

Job Description:

We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.

Key Responsibilities:

Develop and deploy GenAI and Agentic AI applications.
Build RAG pipelines, LLM workflows, and AI agents.
Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
Implement tool calling, context retrieval, and LLM orchestration.
Integrate AI solutions with APIs and cloud platforms.
Work with AWS/Azure/GCP, Docker, and CI/CD.

Required Skills:

Strong Python programming skills.
3+ years of GenAI/Agentic AI experience.
RAG and LLM orchestration.
LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
MCP and A2A knowledge.
Cloud, APIs, Docker, and CI/CD experience.

Preferred Experience:

Hands-on experience building and deploying production-ready AI solutions.

Job Description:

We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.

Key Responsibilities:

Develop and deploy GenAI and Agentic AI applications.
Build RAG pipelines, LLM workflows, and AI agents.
Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
Implement tool calling, context retrieval, and LLM orchestration.
Integrate AI solutions with APIs and cloud platforms.
Work with AWS/Azure/GCP, Docker, and CI/CD.

Required Skills: