Required. AI & Data Analytics Engineer AI & Data Analytics Engineer

Job Summary

We are seeking an innovative AI Data Analytics Engineer to design, develop, and deploy next-generation AI-powered analytics platforms that transform complex enterprise data into actionable business insights. This role combines expertise in Artificial Intelligence, Data Engineering, Analytics, and Business Intelligence to build intelligent, scalable, and production-ready solutions.

The ideal candidate will have strong experience in Python development, enterprise data engineering, Large Language Models (LLMs), and modern analytics technologies. You will collaborate with product managers, software engineers, data engineers, and business stakeholders to build AI-driven applications that enable intelligent decision-making through conversational analytics, semantic data models, and advanced data pipelines.

Experience: 5+ Years

Location: Bangalore

Work Environment: Office / Hybrid - 2 to 3 days from client office

Responsibilities AI Application Development

• Design, develop, and deploy production-grade AI applications using Large Language Models (LLMs).
• Build agentic AI systems utilizing function-calling architectures, structured outputs, and advanced prompt engineering techniques.
• Develop and orchestrate multi-agent AI workflows for planning, reasoning, data retrieval, and intelligent response generation.
• Optimize AI workflows through model orchestration, routing strategies, fallback mechanisms, and prompt optimization.
• Develop evaluation frameworks to measure AI quality, response accuracy, SQL generation, routing performance, and overall system effectiveness.

Data Engineering

• Design and develop scalable ETL/ELT pipelines to ingest, transform, validate, and manage enterprise datasets.
• Integrate structured, semi-structured, and geospatial data from multiple enterprise systems.
• Build and maintain semantic data layers including schema normalization, metadata mapping, and enterprise data models.
• Implement data quality, validation, lineage, and governance best practices.
• Optimize data processing pipelines for scalability, performance, and reliability.

Analytics Business Intelligence

• Develop conversational analytics platforms and AI-assisted business intelligence applications.
• Build interactive dashboards and data visualization solutions using modern BI tools.
• Design scalable analytical models that enable self-service reporting and enterprise decision support.
• Collaborate with business stakeholders to translate analytical requirements into impactful AI and data solutions.

Collaboration Platform Engineering

• Partner with Product Managers, Data Engineers, Software Engineers, and business teams to deliver end-to-end AI solutions.
• Participate in architecture discussions, technical design reviews, and solution planning.
• Ensure AI and analytics platforms are secure, scalable, reliable, maintainable, and production-ready.
• Document solution designs, implementation approaches, and technical best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field.
• Minimum 5**+ years** of experience in Artificial Intelligence, Machine Learning, Data Engineering, Analytics, or related disciplines.
• 3+ years of strong hands-on experience developing production-grade applications using Python.
• 3+ years pf experience working with structured, semi-structured, and geospatial datasets.
• Experience building enterprise analytics platforms or decision-support systems.
• Strong analytical thinking and problem-solving skills.
• Excellent written and verbal communication skills with the ability to work effectively across technical and business teams.

Required Technical Skills Programming

• Python
• SQL
• Pydantic

Artificial Intelligence LLMs

• OpenAI GPT
• Google Gemini
• Anthropic Claude
• Function Calling
• Structured Outputs
• Prompt Engineering
• Agentic AI
• Multi-Agent Architectures

Data Engineering

• ETL/ELT Pipeline Development
• DuckDB
• PostgreSQL
• Databricks
• AWS S3
• Enterprise Data Platforms
• Data Modeling
• Metadata Management
• Data Quality Frameworks

Analytics Business Intelligence

• Power BI
• Streamlit
• Tableau
• Interactive Dashboards
• Conversational Analytics
• Business Intelligence
• Semantic Data Models

Preferred Qualifications

• Experience designing enterprise AI solutions leveraging Retrieval-Augmented Generation (RAG) and semantic search.
• Experience integrating AI capabilities into enterprise applications and business workflows.
• Familiarity with cloud-native AI and analytics architectures on AWS or Azure.
• Knowledge of AI governance, model evaluation, observability, and responsible AI best practices.
• Experience with API integrations, microservices, and scalable enterprise application architectures.