Senior Generative AI & Full Stack Engineer

Job Location: Pune

Location Flexibility: Primary Location Only

Req Id: 4493

Posting Start Date: 12/12/25

Role: Senior Generative AI & Full Stack Enginee

rExperience: 5+yr

sShifts: 8am- 5pm IST

.Work Location: Pun

e

1. List of Ski

llsCategory Ski

llsStrong Expertise- Python Programm

ing- Machine Learning & Deep Learn

ing- Natural Language Processing (N

LP)- Generative AI Solution Developm

ent- Full Stack Development (Frontend + Backe

nd)- Model Fine-Tuning & Optimizat

ion- MLOps & CI/CD Pipeli

nes- Data Science & Statist

icsBasic Proficiency- Conversational AI (Chatbots, LangChain, AutoG

en)- Data Engineering & Processing (Spark, Pandas, NumPy, PyTorch, TensorFl

ow)- Cloud AI Platforms (AWS, Azu

re)- API Development & Integrat

ionKnowledge Only- Open-source AI contributi

ons- Software Design Princip

les- AI Ethics & Bias Mitigat

ion- Agile/Scrum Development Practi

ces
2. Primary Sk

illsGenerative AI & Large Language Model (LLM) based Solution Develop
mentDesign, develop, and fine-tune cutting-edge generative AI models, including open-source LLMs, for real-world, scalable applicati
ons.Natural Language Processing (
NLP)Apply NLP techniques for tasks like text generation, summarization, translation, entity recognition, and sentiment analysis using frameworks like Hugging Face, spaCy, and OpenAI
GPT.Full Stack Develop
mentDesign and implement scalable end-to-end applications integrating AI models using modern front-end (React, Angular, etc.) and back-end (FastAPI, Django, Node.js) technolog
ies.Python Programming for AI & Web Applicat
ionsLeverage Python for both AI algorithm development and backend services, ensuring seamless integration between machine learning models and application lo
gic.Machine Learning & Deep Lear
ningApply supervised, unsupervised, and reinforcement learning techniques using libraries such as Scikit-learn, TensorFlow, and PyTo
rch.Model Fine-Tuning & Optimiza
tionCustomize pre-trained models with domain-specific data, improving accuracy and efficiency in inference workfl
ows.ML Ops & Production-Ready AI Deploy
mentBuild and manage robust ML Ops pipelines including Docker, Kubernetes, and CI/CD for continuous deployment, monitoring, and model managem

ent.
3. Secondary S

killsConversational AI & Chatbot Frame
worksDevelop AI-powered virtual assistants using LangChain, AutoGen, or similar libraries to meet enterprise conversational requirem
ents.Cloud AI Platform Integr
ationDeploy and scale applications using cloud platforms such as Azure, or AWS for secure, high-performance model hos
ting.Data Engineering & Preproce
ssingCollaborate with data engineers to process and manage large datasets with tools like Apache Spark, Pandas, and SQL for training and evalua
tion.API Development & Integr
ationBuild RESTful APIs to expose AI capabilities and enable seamless integration with business systems and UI compon
ents.AI Research, Innovation & Open-Source Contrib
utionStay updated with the latest trends in generative AI and contribute to open-source AI projects to stay ahead in innovation and de
sign.AI Ethics & Bias Mitig
ationAwareness of ethical AI design and practices to ensure responsible AI deployments and fair model behaviour in production environm

ents.

Relocation Suppor

ted: NoVisa Sponsorship Appro

ved: No