GenAI / AI-ML Engineer

Two95 International Inc.; Gurugram District; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

Two95 International Inc. in Gurugram seeks an experienced GenAI/AI-ML Engineer to design, develop, and deploy scalable AI-powered applications, including production-ready RAG pipelines and LLM-based services, with AWS deployment in a hybrid setup.

You will build REST APIs with FastAPI, work on prompt engineering and multi-agent workflows, and collaborate with data engineering, DevOps, and product teams to deliver reliable AI solutions.

Qualifications

• Minimum 1 year of GenAI/LLM project experience.
• Experience building production-ready RAG pipelines.
• Strong Python and REST API development skills.
• Experience with AWS and cloud deployments.
• Prompt engineering and multi-agent systems experience.

Responsibilities

• Design, develop, test, and deploy scalable AI/ML/GenAI solutions.
• Build and optimize Retrieval-Augmented Generation pipelines with embeddings and vector databases.
• Develop LLM-powered apps using prompt engineering, AI agents, LangGraph, and multi-agent workflows.
• Fine-tune, evaluate, deploy, and monitor ML/DL models in production.
• Build REST APIs and backend services using FastAPI.
• Design data preprocessing, feature engineering, and model-training pipelines.
• Integrate structured/unstructured data for context-aware AI solutions.
• Implement semantic search and document retrieval architectures.
• Evaluate RAG and GenAI with quality/performance metrics.
• Collaborate with Data Eng, DevOps, Product, and cross-functional teams.
• Ensure scalability, reliability, security, and performance in production.

Skills

Python

SQL

REST APIs

Agile

PyTorch

TensorFlow

Keras

NLP

Education

Bachelor's/Master's in CS or related

Tools

Docker

Git

JIRA

CI/CD

FastAPI

LangChain

LangGraph

OpenAI APIs

Hugging Face

Job description

Role Overview

We are looking for an experienced GenAI / AI-ML Engineer with strong hands-on expertise in Python, machine learning, deep learning, Large Language Models, Retrieval-Augmented Generation, and agentic AI systems. The selected candidate will be responsible for designing, developing, and deploying scalable AI-powered applications. The role requires practical experience in building production-ready RAG pipelines, LLM-powered applications, REST APIs, machine-learning models, and cloud-based AI solutions using AWS.

Key Responsibilities

• Design, develop, test, and deploy scalable AI, machine-learning, deep-learning, and Generative AI solutions.
• Build and optimise Retrieval-Augmented Generation pipelines using modern frameworks, embedding models, and vector databases.
• Develop LLM-powered applications using prompt engineering, AI agents, LangGraph, and multi-agent workflows.
• Fine-tune, evaluate, deploy, and monitor machine-learning and deep-learning models.
• Build REST APIs and backend services for AI applications using FastAPI or similar frameworks.
• Design data-preprocessing, feature-engineering, model-training, and model-evaluation pipelines.
• Integrate structured and unstructured data sources to deliver accurate and context-aware AI solutions.
• Implement semantic search and document-retrieval architectures.
• Evaluate RAG and Generative AI solutions using appropriate quality and performance metrics.
• Collaborate with Data Engineering, DevOps, Product, and other cross-functional teams.
• Ensure the scalability, reliability, security, and performance of AI applications in production environments.
• Follow software-engineering best practices, coding standards, version-control processes, and Agile methodologies.
• Troubleshoot model, API, data-pipeline, and production-performance issues.

Mandatory Skills

Programming and Backend Development

• Strong hands-on experience in Python.
• Strong working knowledge of SQL.
• Experience developing REST APIs using FastAPI or similar Python frameworks.
• Good understanding of object-oriented programming, modular development, testing, and software-engineering best practices.
• Experience working in Agile development environments.

Machine Learning and Deep Learning

Hands-on experience with:

• Scikit-learn
• TensorFlow
• PyTorch
• Keras

Strong understanding of:

• Regression
• Classification
• Clustering
• Feature engineering
• Data preprocessing
• Model evaluation
• Hyperparameter tuning
• Model deployment and monitoring

NLP and Generative AI

• Minimum one year of hands-on experience working on GenAI or LLM-based projects.
• Strong understanding of Large Language Models and Natural Language Processing concepts.
• Experience in prompt engineering and prompt optimisation.
• Hands-on experience designing and implementing RAG architectures.
• Experience building agentic AI or multi-agent applications.
• Practical experience with:
  • LangChain
  • LangGraph
  • OpenAI APIs
  • Hugging Face
  • LangSmith

RAG and Vector Databases

• Experience working with vector databases and similarity-search technologies, including:
  • Pinecone
  • FAISS
• Knowledge of embedding models, chunking strategies, semantic search, document retrieval, and reranking.
• Experience evaluating RAG solutions using metrics or frameworks such as:
  • RAGAS
  • BLEU
  • ROUGE

AWS and DevOps

Hands-on experience with AWS services such as:

• Amazon EC2
• Amazon S3
• Amazon SageMaker
• Amazon Bedrock

Experience working with:

• Docker
• Git
• JIRA
• CI/CD pipelines

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
• Experience deploying AI and LLM applications in production environments.
• Understanding of LLM observability, hallucination control, guardrails, latency optimisation, and cost optimisation.
• Experience integrating enterprise data sources with GenAI applications.
• Strong analytical, problem-solving, communication, and stakeholder‑management skills.

Candidate Eligibility

• Candidates must have 4–6 years of overall professional experience.
• At least one year of practical GenAI or LLM project experience is mandatory.
• Candidates must be immediate joiners.
• Candidates should be based in Noida, Gurugram, Delhi, or another NCR location.
• Candidates must be comfortable working in a hybrid model from the Gurugram office.
• Candidates should be available for an interview on August 1 or August 3, 2026.