Engineering Intern – Transport Analytics
LocationChennai
Typeinternship
SeniorityEntry
DepartmentEngineering
Company size201–500 people
PostedSep 28, 2026 · 2w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline
Solid foundational knowledge and hands-on project experience in both Python and Java
Practical understanding of relational database systems (SQL/NoSQL) and experience building web applications connected via backend DB APIs
Familiarity with Generative AI concepts, LLM application architectures, or emerging Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI, or tool-use patterns)
A structured, analytical approach to troubleshooting and breaking down ambiguous business problems into clear technical components
Prior internship, open-source contribution, or academic project experience involving data warehousing, ETL pipelines
Basic understanding of cloud infrastructure (AWS /Azure) and containerization tools like Docker
Excellent verbal and written communication skills with the ability to articulate technical concepts to non-technical business partners
Skills
Python
Java
SQL
NoSQL
LangChain
AutoGen
CrewAI
AWS
Azure
Docker
Job Description:
Role Summary & Core Objective
The Transport Analytics team serves as the backbone data warehouse ecosystem powering our suite of inland transport products. We bridge complex supply chain logistics with high-performance data systems to solve real-world operational challenges. We are seeking a high-octane Engineering Intern who combines strong core software engineering fundamentals with a curiosity for modern AI paradigms to drive quantifiable business outcomes: revenue growth, cost reduction, or elevated customer satisfaction.
Key Responsibilities
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Full-Stack & API Development: Design, build, and maintain lightweight web applications and RESTful APIs that interface directly with our analytics database ecosystem.
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Data & Analytics Integration: Query, transform, and leverage data warehouse pipelines to feed user-facing analytical tools and internal operational dashboards.
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AI & Agentic Experimentation: Assist in prototyping modern AI workflows—exploring Agentic AI frameworks, LLM integrations, and intelligent automation to solve transport analytics challenges.
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Cross-Functional Problem Solving: Work closely with product managers and business stakeholders to translate complex business problems into reliable, efficient engineering solutions.
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Rapid Prototyping: Adapt quickly to changing product needs, delivering functional proof-of-concepts (PoCs) that can be validated directly with end-users.
Qualifications & Skill Requirements
Minimum Qualifications
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Education: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline.
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Polyglot Programming: Solid foundational knowledge and hands-on project experience in both Python and Java.
•
Database & Web Fundamentals: Practical understanding of relational database systems (SQL/NoSQL) and experience building web applications connected via backend DB APIs.
•
Modern AI Awareness: Familiarity with Generative AI concepts, LLM application architectures, or emerging Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI, or tool-use patterns).
•
Problem-Solving Mindset: A structured, analytical approach to troubleshooting and breaking down ambiguous business problems into clear technical components.
Preferred Qualifications
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Logistics & Data Pipelines: Prior internship, open-source contribution, or academic project experience involving data warehousing, ETL pipelines.
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Cloud & DevOps Tools: Basic understanding of cloud infrastructure (AWS /Azure) and containerization tools like Docker.
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Communication Skills: Excellent verbal and written communication skills with the ability to articulate technical concepts to non-technical business partners.
What Success Looks Like (KPIs & Impact)
During your internship, success will be measured by your ability to deliver end-to-end engineering solutions that drive tangible output across at least one of these core business pillars:
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Cost Reduction: Automating inefficient manual workflows or optimizing query performance to cut cloud infrastructure and operational overhead.
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Revenue Growth: Building feature prototypes or analytics tools that unlock new customer capabilities or identify upsell opportunities across transport products.
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Customer Satisfaction (CSAT): Resolving latency bottlenecks and improving data visibility for transport stakeholders to deliver a seamless user experience.
Why Join Us?
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High Ownership & Impact: Work on live data infrastructure and customer-impacting products rather than isolated side projects.
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Mentorship & Growth: Collaborate directly with senior data engineers, software architects, and technical product managers who are invested in your career.
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Cutting-Edge Tech Stack: Get hands-on exposure at the intersection of enterprise data warehouses, full-stack web development, and next-gen AI frameworks.
Legal
Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.