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 highly motivated Data & AI Engineer to design, build, and deploy data-driven and AI-powered solutions for enterprise customers and internal platforms.
In this role, you will work across the entire data and AI lifecycle—from data engineering and preparation to machine learning, MLOps, Generative AI, and production deployments. You will collaborate with solution architects, cloud engineers, product teams, and customer stakeholders to deliver scalable, cloud-native solutions on AWS.
The ideal candidate combines strong data engineering fundamentals with machine learning expertise and a passion for building next-generation AI applications. This role also offers exposure to Generative AI, Agentic AI, and modern AI engineering practices that are shaping the future of enterprise technology.

Key Responsibilities

Data Engineering & Pipeline Development

  • Design, build, and maintain scalable data pipelines for customer and internal projects.
  • Develop data ingestion, transformation, and processing workflows for structured and unstructured data.
  • Work with relational, NoSQL, and analytical data stores.
  • Ensure data quality, reliability, scalability, and performance across data platforms.
  • Optimize data architectures and processing frameworks for efficiency and cost-effectiveness.

Machine Learning & Applied AI

  • Design, train, evaluate, and deploy machine learning and deep learning models for real-world use cases.
  • Develop solutions across classification, regression, forecasting, recommendation systems, NLP, and predictive analytics.
  • Perform feature engineering, model evaluation, hyperparameter tuning, and experimentation.
  • Integrate machine learning models into production environments.

Generative AI & Agentic AI

  • Design and develop Generative AI applications using Large Language Models (LLMs).
  • Build Retrieval-Augmented Generation (RAG) solutions, enterprise AI assistants, and intelligent automation workflows.
  • Develop and optimize prompts, workflows, and reasoning patterns for AI applications.
  • Experiment with Agentic AI frameworks and AI orchestration platforms.
  • Evaluate and benchmark foundation models for various business use cases.

AWS Data & AI Solutions

  • Design and implement cloud-native AI and analytics solutions on AWS.
  • Work extensively with AWS Data & AI services including:
    • Amazon SageMaker
    • Amazon Bedrock
    • AWS Glue
    • Amazon Athena
    • Amazon Redshift
    • Amazon OpenSearch
    • AWS Lambda
    • Amazon S3
  • Build scalable, secure, and production-ready AI solutions on AWS.

MLOps & Production Deployment

  • Design and implement MLOps workflows for model lifecycle management.
  • Build automated training, deployment, monitoring, and retraining pipelines.
  • Implement model versioning, governance, observability, and performance monitoring.
  • Collaborate with DevOps and CloudOps teams to operationalize AI workloads.

Customer Engagement & Solution Delivery

  • Participate in customer discovery workshops, requirement gathering sessions, and solution demonstrations.
  • Translate business requirements into scalable data and AI architectures.
  • Collaborate with customer stakeholders to deliver measurable business outcomes.
  • Present technical recommendations and solution approaches to both technical and non-technical audiences.

Collaboration & Innovation

  • Work closely with CloudOps, DevOps, Product, and Architecture teams.
  • Mentor junior engineers and interns through technical guidance and code reviews.
  • Document architectures, workflows, experiments, and best practices.
  • Research emerging technologies and contribute innovative ideas to customer and internal projects.
  • Contribute reusable frameworks, accelerators, and reference implementations to 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
    • Statistics
    • Mathematics
    • Related technical disciplines
  • 3–6 years of hands-on experience in Data Engineering, Machine Learning, Applied AI, or Data Science.
  • Strong programming skills in Python.
  • Hands-on experience with machine learning frameworks such as:
    • Scikit-Learn
    • TensorFlow
    • PyTorch
  • Strong understanding of:
    • Data Structures
    • Algorithms
    • Software Engineering Principles
    • Machine Learning Fundamentals
  • Proven experience working with SQL, NoSQL databases, and large-scale datasets.
  • Experience with modern data platforms and big data technologies such as:
    • Apache Spark
    • Kafka
    • Snowflake
    • Similar distributed data systems
  • Hands-on experience with AWS Data & AI services including:
    • Amazon SageMaker
    • Amazon Bedrock
    • AWS Glue
    • Amazon Athena
    • Amazon Redshift
    • Amazon OpenSearch
  • Experience implementing MLOps practices using tools such as:
    • MLflow
    • Kubeflow
    • SageMaker Pipelines
    • CI/CD for Machine Learning
  • Hands-on experience with one or more GenAI frameworks including:
    • LangChain
    • LangGraph
    • Hugging Face
    • OpenAI APIs
    • Anthropic APIs
    • CrewAI
    • Similar AI orchestration frameworks
  • Strong understanding of:
    • Large Language Models (LLMs)
    • Prompt Engineering
    • Retrieval-Augmented Generation (RAG)
    • AI Application Development
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, or OpenSearch Vector Engine.
  • Knowledge of data governance, data security, and compliance frameworks.
  • Strong analytical and problem-solving capabilities.
  • Familiarity with Agentic AI architectures and multi-agent systems.
  • AWS Professional-level certification.
  • Excellent communication and stakeholder management skills.
  • AWS AI/ML Specialty Certification or equivalent demonstrated expertise.

Desired but Not Must-Have Qualifications

  • Experience building enterprise AI assistants and conversational AI applications.
  • Experience with Computer Vision, NLP, or advanced deep learning architectures.
  • Contributions to open-source projects, research publications, or technical communities.
  • Participation in hackathons, Kaggle competitions, or innovation programs.

What We're Looking For

  • Strong engineering mindset with a passion for solving business problems using data and AI.
  • Curiosity to experiment with emerging AI technologies and frameworks.
  • Ability to balance innovation with practical business outcomes.
  • Strong ownership and accountability for project delivery.
  • Excellent collaboration and communication skills.
  • Continuous learner who stays updated with advancements in AI, Data Engineering, and Cloud technologies.
  • Customer-centric approach with a focus on delivering measurable value.

What Success Looks Like

  • Successful delivery of production-grade Data & AI solutions.
  • High-quality data pipelines and scalable AI architectures.
  • Effective deployment and operationalization of machine learning and GenAI solutions.
  • Strong customer satisfaction and measurable business impact.
  • Contributions to innovation, accelerators, and reusable frameworks.
  • Continuous improvement of AI engineering and MLOps practices.
  • Growth into technical leadership responsibilities within the Data & AI practice.

Why Join Comprinno

  • Be part of a fast-growing Data Analytics & AI practice within one of the leading AWS partners in APJ.
  • Work on cutting-edge AI, GenAI, Agentic AI, and cloud-native solutions.
  • Gain exposure to diverse customer challenges across industries.
  • Learn directly from AWS-certified architects, AI practitioners, and technology leaders.
  • Build expertise in Data Engineering, Machine Learning, GenAI, and MLOps.
  • Accelerate your growth through continuous learning, AWS certifications, and mentorship programs.
  • Contribute to innovative products such as Tevico and future AI-powered platforms.
  • Join a collaborative culture that values ownership, innovation, learning, and excellence.
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