Gen AI Developer

Role: Gen AI Developer

Required Technical Skill Set (Must Have): Gen AI / LLM /Agentic AI

Desired Experience Range:6 to 8 Yrs

Location of Requirement: PAN INDIA

Desired Competencies (Technical/Behavioral Competency)

Must-Have

• Strong programming skills in

  Python

  with experience in building ML/NLP applications.
• Hands-on experience with

  Deep Learning

  ,

  Machine Learning

  , and

  Natural Language Processing

  .
• Proficiency in working with

  LLMs

  (e.g., GPT,Gemini, LLaMA, Mistral) and

  RAG

  architecture.
• Experience with

  Agentic AI

  frameworks and autonomous agent design.
• Familiarity with

  FastAPI

  for building RESTful APIs.
• Experience with

  CI/CD pipelines

  and deploying solutions on

  Azure Cloud, GCP and AWS

• Solid understanding of data structures, algorithms, and software engineering principles.
• Bachelors or master’s degree in computer science, AI, Data Science, or related field.
• Retrieval Augmented Generation (RAG): Hands-on experience in building and optimizing RAG pipelines from scratch
• Expert-level proficiency and hands-on experience with LangChain and/or LlamaIndex for building complex LLM applications, including chains, agents, memory, and tool integration.

Good-to-Have

• Excellent Communication Skills
• Strong Software Engineering Background (Productionizing the models)
• Hands-on experience with data science tools
• Problem-solving aptitude
• Analytical mind and great business sense

Responsibility of / Expectations from the Role

• Design and implement GenAI solutions leveraging LLMs, RAG pipelines, and Agentic AI architectures.
• Develop and fine-tune deep learning models for NLP tasks using frameworks like PyTorch or TensorFlow.
• Build scalable APIs using FastAPI to serve AI models and integrate with enterprise systems.
• Collaborate with data scientists and ML engineers to deploy models using CI/CD pipelines on Azure.
• Optimize model performance and ensure robustness in production environments.
• Stay updated with the latest research and advancements in generative AI and deep learning.

• Scalability & Performance:

  Ability to write efficient code and consider scalability and latency implications for Gen AI applications.

• Containerization:

  Practical experience with

  Docker

  for packaging and deploying applications.