Data & AI Engineer

About Comprinno Comprinno is a NASSCOM-incubated company headquartered in Bangalore, with offices in Pune, Coimbatore, and the United States. We specialize in cloud transformation, DevOps, infrastructure automation, and Artificial Intelligence, enabling organizations to build scalable, secure, and high-performing cloud environments on AWS. Our flagship SaaS platform, Tevico , offers intelligent cloud governance and observability for AWS workloads. It helps enterprises improve uptime, reduce costs, and ensure compliance by proactively detecting anomalies and triggering automated remediation workflows. As an AWS Advanced Consulting Partner, Comprinno helps organizations migrate, modernize, secure, and operate cloud environments while adopting emerging technologies such as Generative AI and Agentic AI. About the Role We are seeking a motivated and technically strong Data & AI Engineer to contribute to data-driven and AI-powered solutions for enterprise customers and internal platforms. In this role, you will work across data engineering, machine learning, Generative AI, and cloud-native analytics solutions while collaborating with architects, senior engineers, and customer teams. You will gain hands-on experience building production-grade data pipelines, AI applications, and cloud-native analytics solutions using AWS technologies. This role is ideal for professionals who want to build a career in Data Engineering, Machine Learning, Applied AI, MLOps, and Generative AI. Key Responsibilities Data Engineering & Analytics • Assist in building and maintaining data pipelines for customer and internal projects. • Perform data preparation, cleansing, transformation, and feature engineering activities. • Work with structured and unstructured datasets from multiple sources. • Support development of scalable data processing workflows and analytics solutions. • Ensure data quality, reliability, and consistency across projects. Machine Learning & Applied AI • Support development, training, testing, and deployment of machine learning models. • Participate in model evaluation, experimentation, and optimization activities. • Work on use cases involving: • Predictive Analytics • Classification • Forecasting • Recommendation Systems • Natural Language Processing (NLP) • Assist in integrating AI and ML solutions into production environments. Generative AI & Prompt Engineering • Experiment with Large Language Models (LLMs) and Generative AI frameworks. • Assist in building AI assistants, RAG applications, and GenAI-powered workflows. • Design, test, and optimize prompts for business use cases. • Evaluate model outputs and improve response quality through prompt engineering techniques. • Explore emerging AI tools, frameworks, and orchestration platforms. AWS Data & AI Services • Work with AWS services such as: • Amazon SageMaker • Amazon Bedrock • AWS Glue • Amazon Athena • Amazon Redshift • Amazon OpenSearch • AWS Lambda • Amazon S3 • Assist in deploying and managing data and AI workloads on AWS. Collaboration & Innovation • Collaborate with CloudOps, DevOps, Product, and Architecture teams. • Participate in customer projects and solution implementation activities. • Document workflows, experiments, and technical approaches. • Research new technologies and contribute ideas to innovation initiatives. • Contribute to reusable assets, templates, and accelerators within the Data & AI practice. Required Qualifications & Skills • Bachelor's or Master's degree in (B.E./B.Tech./M.E./M.Tech.): • Computer Science • Data Science • Artificial Intelligence • Machine Learning • Statistics • Mathematics • Related technical disciplines • 0–2 years of experience in Data Science, Machine Learning, Data Engineering, Applied AI, or related fields. • Strong programming skills in Python. • Familiarity with: • Pandas • NumPy • Scikit-Learn • TensorFlow or PyTorch • Good understanding of: • Data Structures • Algorithms • Statistics • Machine Learning Fundamentals • Software Engineering Principles • Experience working with SQL and relational databases. • Familiarity with NoSQL databases and large datasets. • Familiarity with GenAI frameworks including: • LangChain • LangGraph • Hugging Face • OpenAI APIs • Anthropic APIs • Understanding of: • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Application Development • Understanding of cloud computing concepts. • Strong analytical and problem-solving abilities. • Good communication and collaboration skills. • Curiosity and passion for learning emerging technologies. Desired Qualifications & Skills • Exposure to AWS Data & AI services such as SageMaker, Bedrock, Glue, Athena, or Redshift. • Familiarity with Spark, Kafka, Snowflake, or similar data platforms. • Exposure to MLOps concepts and tools such as MLflow, Kubeflow, or SageMaker Pipelines. • Participation in: • Hackathons • Kaggle Competitions • Research Projects • Open Source Contributions • AWS AI Practitioner, AWS Machine Learning Engineer Associate, or equivalent cloud certifications. What We're Looking For • Strong analytical mindset and problem-solving capabilities. • Passion for Data, AI, and emerging technologies. • Curiosity to experiment and learn continuously. • Strong ownership and execution mindset. • Ability to work effectively in collaborative environments. • Good communication and stakeholder interaction skills. • Desire to build expertise in Data Engineering, Machine Learning, GenAI, and MLOps. What Success Looks Like • Successfully contributes to customer and internal Data & AI projects. • Demonstrates strong growth in machine learning, data engineering, and AI engineering skills. • Builds proficiency in AWS Data & AI services. • Effectively develops and supports AI-powered solutions. • Contributes reusable assets, accelerators, and best practices. • Demonstrates learning agility and readiness for more advanced technical responsibilities. • Progresses toward becoming