Data Scientist

Data Scientist- Educational Qualifications
• Bachelors or Master’s degree (B.E./B.Tech/M.Tech/MCA) in Computer Science, Electronics & Communication, Electrical Engineering, or a related discipline.
• A Master’s degree in Computer Science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly desirable.
Experience
• 5+ years of overall IT experience, including at least 5+ years of hands-on experience in Data Science.
Must-Have Technical Skills
• Strong Python programming skills with practical experience using deep learning frameworks such as TensorFlow and PyTorch.
• Experience in data preprocessing, data augmentation, and managing large-scale image and video datasets for model development.
• Strong understanding of transformer architectures, RNNs, transfer learning techniques, vision transformer models (e.g., ViT), and fine-tuning of language models.
• Mandatory exposure to Natural Language Processing (NLP) techniques.
• Experience building AI agents using frameworks such as LangGraph.
• Ability to design and optimize prompt engineering workflows for large language models (e.g., GPT, Claude, LLaMA).
• Strong proficiency in Python and up-to-date software development best practices.
• Knowledge of enterprise-level AI security, compliance, and governance requirements.
• Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated model deployment.
• GenAI, agentic workflows, RAG pipelines
Nice-to-Have Technical Skills
• Understanding of and hands-on experience with Convolutional Neural Networks (CNNs) and Reinforcement Learning.
Cloud & Infrastructure
• Strong expertise in Databricks and the Azure cloud ecosystem.
• Experience working in UNIX/Linux environments, including the use of command-line tools for scripting and automation.
Soft Skills
• Strong analytical thinking and problem-solving capabilities.
• Excellent communication skills, including interpersonal, written, visual (presentations), and verbal communication.
• Ability to collaborate effectively with cross-functional teams and mentor junior team members.

AI Engineer- We are seeking a AI Engineer to build and deliver production-grade agentic AI systems for enterprise use. The engineer will develop multi-agent workflows, integrate large language models into existing enterprise systems, and support the deployment and automation needed to run them reliably and securely in production.
This is a hands-on engineering engagement. The work centers on building agents, orchestration logic, and supporting infrastructure that performs under real production workloads, not on proof-of-concept or advisory work.

Scope of Work
• Build AI agents and multi-agent systems using frameworks with LangGraph and LangChain tools.
• Develop and tune prompt engineering workflows across multiple LLMs (GPT, Claude, LLaMA), balancing reliability, cost, and latency.
• Develop REST APIs, WebSocket services, and event-driven pipelines for real-time AI services that remain stable under load.
• Automate testing and releases through Jenkins CI/CD, and maintain code and documentation standards using Git, Jira, and Confluence.
• Deployment of AI Application in enterprise adhering to best practices
• Use AI-augmented development tools such as Claude Code and Codex to accelerate delivery.
• Coordinate with platform, security, and product teams to deliver scalable, secure deployments.

Must-Have Skills
• 4-6 years in Machine Learning, AI, or a related field, with production systems delivered.
• At least 1 year building custom Agentic AI applications
• Strong Python skills and sound modern development practices.
• Hands-on experience with LLMs and prompt engineering across the full application lifecycle.
• Demonstrated experience building AI agents with LangGraph.
• Familiarity with at least one enterprise cloud AI platform for building and deploying agentic applications, such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise, including cloud-native deployment practices.
• Working knowledge of REST APIs, WebSockets, and event-driven systems.
• Proficiency with CI/CD tooling (Jenkins) and version control (Git).
• Fluency with AI-augmented development tools for rapid prototyping.
• Strong written and verbal communication, an analytical approach to problem-solving, and the ability to work independently within a cross-functional team.
• Data layer curations and integration with source system for agentic application

Good-to-Have Skills
• Familiarity with Databricks.
• Exposure to MLOps/LLMOps workflows and application monitoring.
• Knowledge of enterprise security, compliance, and governance for AI systems.
• Familiarity with code and model lifecycle management practices.