Generative AI Engineer

Company:
Nexoria Techworks

Location:
Bangalore, Hyderabad, Pune, Noida

Experience:
3+ Years

Employment Type:
Full-Time, Onsite/Hybrid

About Nexoria Techworks

Nexoria Techworks is a rapidly growing technology company focused on building intelligent, scalable, and high-impact digital solutions powered by Artificial Intelligence. We work on cutting-edge innovations across AI, automation, and data-driven systems that help organizations accelerate digital transformation. Our mission is to create next-generation AI-driven platforms that deliver measurable business outcomes.

We are now expanding our AI team and looking for an experienced
Generative AI Engineer
with strong hands-on experience in building and deploying advanced generative models and LLM-based applications.

Role Overview

The Generative AI Engineer will be responsible for designing, training, and optimizing AI models that generate text, images, audio, or other content. This role requires a strong understanding of deep learning architectures, NLP systems, transformer-based models, and their application to real-world problems. The ideal candidate should have prior experience implementing and scaling generative models in production environments.

Key Responsibilities

• Design, develop, and fine-tune
  Generative AI models
  such as Large Language Models (LLMs), diffusion models, or transformers for text, image, or multimodal outputs.
• Build
  Retrieval-Augmented Generation (RAG)
  pipelines using vector databases like FAISS, Pinecone, or Chroma.
• Develop and implement
  prompt engineering strategies
  and optimization frameworks for task-specific outputs.
• Collaborate with the product and engineering teams to
  integrate AI models into scalable systems and APIs
  .
• Conduct research and experimentation on
  state-of-the-art generative architectures
  including GPT, LLaMA, Mistral, and Stable Diffusion.
• Develop automation pipelines using
  LangChain, Hugging Face Transformers
  , or equivalent frameworks.
• Deploy and monitor models using
  cloud platforms
  such as AWS, GCP, or Azure, ensuring performance, reliability, and cost-efficiency.
• Implement
  MLOps practices
  for model training, evaluation, deployment, and lifecycle management.
• Collaborate closely with data engineers and scientists for data collection, preprocessing, and feature engineering.
• Document model architectures, training methodologies, and deployment strategies for internal knowledge sharing.

Required Technical Skills

• Proficiency in
  Python
  and experience with AI/ML frameworks like
  PyTorch, TensorFlow, or JAX
  .
• Strong understanding of
  transformer-based architectures
  and
  deep learning fundamentals
  .
• Hands-on experience with
  LLMs (GPT, LLaMA, Falcon, Claude, Mistral, etc.)
  and
  API integration
  .
• Familiarity with
  LangChain
  ,
  Hugging Face Transformers
  , and
  vector search systems
  (FAISS, Pinecone, Chroma, Milvus).
• Experience in
  building and optimizing prompt-based systems
  and
  custom model fine-tuning
  .
• Working knowledge of
  cloud infrastructure and DevOps tools
  (AWS S3, EC2, Lambda, Docker, Kubernetes).
• Proficiency with
  MLOps tools
  such as MLflow, DVC, or Weights & Biases.
• Understanding of
  data security, scalability
  , and
  API versioning principles
  .
• Bonus: Experience in
  text-to-image (Stable Diffusion, DALL·E)
  or
  text-to-speech/speech-to-text
  systems (Whisper, ElevenLabs).

Preferred Qualifications

• Bachelor's or Master's Degree in
  Computer Science, Artificial Intelligence, Data Science, or a related discipline
  .
• Minimum of 3 years of experience in
  machine learning or AI
  , with at least 1 year in
  Generative AI or NLP
  .
• Proven track record of
  building and deploying AI models
  into production.
• Strong problem-solving and analytical skills, with the ability to apply research into practical product implementations.
• Portfolio, GitHub repositories, or research publications demonstrating prior AI/ML projects will be an added advantage.