Senior Software Engineer

Role Overview

We are looking for a dynamic and experienced AI/ML Engineer to join our team as a Full Stack Developer with strong proficiency in React, Java/Python, and AWS Cloud technologies. This role will focus on building scalable applications and integrating AI capabilities for classification and summarization workflows that support product development and architectural initiatives.

Key Responsibilities

.Develop and maintain full-stack applications using React (frontend) and Python (backend).

.Design and implement AI/ML models for text classification, document summarization, and intelligent automation.

.Leverage AWS Cloud services (e.g., SageMaker, Lambda, S3, EC2, DynamoDB) for scalable model training, deployment, and application hosting.

.Collaborate with cross-functional teams to embed AI solutions into product workflows.

.Build reusable components and scalable architecture patterns aligned with enterprise standards.

.Apply modern ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face) to solve business problems.

.Ensure high performance, security, and reliability of deployed solutions.

.Participate in Agile ceremonies and contribute to sprint planning, reviews, and retrospectives.

.Document technical designs, workflows, and model performance metrics.

Required Qualifications

.Bachelor's or Master's degree in Computer Science, Engineering, or related field.

.3-5 years of experience in full-stack development withAI/ML experience

.Proficiency in React, Java, and Python.

.Hands-on experience with NLP techniques for classification and summarization.

.Strong working knowledge of AWS Cloud services and architecture.

.Familiarity with CI/CD pipelines and DevOps practices.

.Excellent problem-solving and communication skills.

Preferred Skills

.Experience with LLMs, RAG pipelines, or transformer-based models.

.Exposure to MLOps practices and model deployment strategies.

.Knowledge of enterprise-grade security and compliance standards.

.Prior experience working in product development or architecture teams.

.Deep learning:An understanding of neural network architectures, such as Convolutional Neural Networks (CNNs) for images and Recurrent Neural Networks (RNNs) for sequential data.

.Natural Language Processing (NLP):Foundational knowledge of text processing techniques for building chatbots, sentiment analysis tools, and other language-based applications.

.Computer vision:Skills in image processing and object detection, valuable for roles in areas like robotics or autonomous systems.

.Generative AI and Prompt Engineering:An emerging area of demand, requiring skills in interacting with and fine-tuning large language models (LLMs).