AI Data Engineer

Actively Reviewing the Applications

Umanist NA

India, Kerala, Thiruvananthapuram Full-Time INR 15–30 LPA

Posted 2 months ago • Apply by April 29, 2026

Job Description

Job Title: AI Data Engineer(Data & ML Pipelines)

Experience: 8–14 Years

Location: Multiple locations across India (Hybrid – 3 days office)

Employment Type: Full-Time,29276

Notice Period: Immediate to 15 days preferred

Role Overview

We are looking for a strong AI Engineer with solid data engineering expertise to design, build, and operationalize scalable data and AI solutions. This role combines advanced AI/ML development with enterprise-grade data pipeline architecture. You will work on real-world AI use cases while ensuring robust, production-ready data platforms.

Key Responsibilities

Architect and maintain scalable data pipelines and enterprise data models for AI, analytics, and BI use cases
Design and optimize ETL/ELT frameworks using modern cloud-based data integration tools
Build and manage cloud data platforms for high-performance analytics
Develop and deploy AI/ML solutions including deep learning, NLP, LLMs, and generative AI
Lead AI experimentation, prototyping, and applied research initiatives
Build end-to-end ML pipelines (data prep → feature engineering → deployment → monitoring)
Implement CI/CD workflows for data and AI pipelines
Create executive dashboards and analytical applications for business insights
Collaborate with cross-functional teams to align technical solutions with business needs
Define and enforce best practices in data quality, governance, security, and observability

Must-Have Skills

Strong hands-on experience with AI/ML techniques including Deep Learning, NLP, and LLMs / Generative AI
Proven experience delivering AI-driven solutions for real business problems
Strong Python expertise for data engineering and machine learning
Hands-on experience with Snowflake for cloud data warehousing and analytics
Experience building data pipelines using modern ETL/ELT tools (e.g., Azure Data Factory or similar)
Strong understanding of enterprise data modeling, data quality, and scalable pipeline design
Experience implementing CI/CD pipelines for ML and data workflows
Experience building dashboards using Power BI or Tableau
Experience working with cloud platforms (Azure preferred; AWS/GCP acceptable)
Ability to translate technical outcomes into business insights
Solid exposure to data engineering + AI engineering together (not purely one side)

Nice-to-Have Skills

Experience with MLOps practices (model deployment, monitoring, observability)
Exposure to telecom/network data (5G, LTE, VoLTE, SMS, usage, roaming, etc.)
Familiarity with vector databases, embeddings, and RAG architectures
Experience integrating LLMs with enterprise systems and data platforms
Experience working in Agile and large enterprise environments

Candidate Requirements

Strong career stability
Notice period within 15 days
Experience aligned with stated years of experience
Compensation expectations aligned with the budget range

Interview Process

2 Technical Rounds
1 Client/Stakeholder Round

Skills: nlp,cloud platforms,snowflake,power bi or tableau,python,elt tools,llms,data pipelines,deep learning models,ci/cd pipelines,ai/ml,generative ai