Up Open source developer Jobs – 95 Open Jobs Today

Generative AI Engineer (LLMs | RAG | Python | Machine Learning)
WebSenor —Noida, Uttar Pradesh
- Full-time
- Hybrid work
- Azure
- Computer Science
- Master's degree
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Data Migration Consultant
NTT Ltd —Noida, Uttar Pradesh
- Full-time
- Remote
- Computer Science
- SQL
- Bachelor's degree
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- Azure
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Sara Technologies —Noida, Uttar Pradesh
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VML —Noida, Uttar Pradesh
- Hybrid work
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Ortu Software —Noida, Uttar Pradesh
- Email
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SAP MM with Data Migration Consultant
NTT Ltd —Noida, Uttar Pradesh
- Full-time
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Interactive Mission —Noida, Uttar Pradesh
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Generative AI Engineer (LLMs | RAG | Python | Machine Learning)

WebSenor
Noida, Uttar Pradesh

Quick apply

Job details

Full-time
7 days ago

Qualifications

TensorFlow
CI/CD
Azure
Law
Computer Science
Kubernetes
Git
Google Cloud Platform
MongoDB
Master's degree
Databases
OOP
AWS
Docker
Bachelor's degree
Machine learning
PostgreSQL
Continuous integration
Redis
Azure Certification
REST
Natural language processing
Scrum
APIs
Agile
Data science
Flask
AI
Communication skills
Python
Data Science

Full job description

We are seeking an innovative Generative AI Engineer with strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and Machine Learning. The ideal candidate will be responsible for designing, developing, and deploying AI-powered applications that leverage state-of-the-art language models to solve complex business problems.

The candidate should have hands-on experience with LLM integration, prompt engineering, vector databases, RAG pipelines, machine learning model development, and cloud-based AI services. This role requires close collaboration with data scientists, software engineers, product teams, and business stakeholders to build scalable AI solutions.

Key ResponsibilitiesGenerative AI Development

Design, develop, and deploy Generative AI solutions using modern LLM frameworks.
Build AI-powered applications such as intelligent chatbots, virtual assistants, document processing systems, and content generation platforms.
Integrate foundation models through APIs and open-source frameworks.
Optimize AI applications for scalability, performance, and cost efficiency.
Stay updated with the latest advancements in Generative AI technologies.

Large Language Models (LLMs)

Develop applications utilizing commercial and open-source LLMs.
Fine-tune, evaluate, and optimize language models where applicable.
Design effective prompt engineering strategies for improved model responses.
Implement model monitoring, evaluation, and response quality metrics.
Address AI safety, hallucination reduction, and responsible AI practices.

Retrieval-Augmented Generation (RAG)

Design and implement Retrieval-Augmented Generation (RAG) pipelines.
Build document ingestion, embedding, indexing, and retrieval workflows.
Integrate vector databases for semantic search and knowledge retrieval.
Optimize retrieval accuracy, context management, and response relevance.
Work with structured and unstructured enterprise data sources.

Machine Learning & Data Science

Develop, train, evaluate, and deploy machine learning models.
Perform data preprocessing, feature engineering, and model validation.
Implement NLP and text analytics solutions.
Analyze model performance and improve prediction accuracy.
Collaborate with data engineering teams to build scalable ML pipelines.

Python Development

Develop scalable backend services and AI applications using Python.
Build REST APIs for AI model integration.
Write clean, modular, and maintainable production-grade code.
Develop reusable libraries and automation scripts.
Integrate AI solutions with enterprise applications.

Deployment & MLOps

Deploy AI models to cloud environments and production systems.
Implement CI/CD pipelines for machine learning workflows.
Monitor model performance, usage, and reliability.
Support containerization using Docker and orchestration with Kubernetes (preferred).
Maintain model versioning and experiment tracking.

Collaboration & Innovation

Collaborate with product managers, engineers, and business stakeholders.
Participate in architecture discussions and AI solution design.
Conduct proof-of-concepts (POCs) for emerging AI technologies.
Mentor junior developers and promote AI best practices.

Required SkillsGenerative AI

Generative AI
Large Language Models (LLMs)
Prompt Engineering
AI Agents
Responsible AI

RAG & Knowledge Retrieval

Retrieval-Augmented Generation (RAG)
Vector Databases
Semantic Search
Embeddings
Document Processing

Machine Learning

Machine Learning
Natural Language Processing (NLP)
Deep Learning
Model Training & Evaluation
Feature Engineering

Programming

Python
FastAPI / Flask
REST APIs
Object-Oriented Programming

AI Frameworks

LangChain
LlamaIndex
Hugging Face Transformers
OpenAI APIs
PyTorch
TensorFlow
Scikit-learn

Databases

PostgreSQL
MongoDB
Redis
Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate, or Milvus)

Cloud & DevOps

Microsoft Azure / AWS / Google Cloud Platform (GCP)
Docker
Kubernetes
Git
CI/CD Pipelines

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
4–8 years of experience in Python development and Machine Learning.
Hands-on experience building Generative AI and RAG-based applications.
Strong understanding of NLP, embeddings, vector search, and LLM architectures.
Experience deploying AI applications in cloud environments.
Familiarity with MLOps practices, model monitoring, and experiment tracking.
Excellent analytical, problem-solving, and communication skills.
Experience working in Agile/Scrum development environments.

Preferred Certifications

Microsoft Certified: Azure AI Engineer Associate (AI-102)
Microsoft Certified: Azure Data Scientist Associate (DP-100)
AWS Certified Machine Learning – Specialty
Google Professional Machine Learning Engineer
TensorFlow Developer Certificate (Preferred)
Databricks Certified Machine Learning Professional (Preferred)

Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)

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