Description :

We are hiring for Gen AI Developer - Pan India

Role : Gen AI Developer

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

Desired Experience Range : 4 to 8 Yrs

Location of Requirement : Any

IOU-Detail : Digital-Manufacturing

Desired Competencies (Technical/Behavioral Competency) :

- 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 masters 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.

- 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.