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Role Overview:At Digitraly, we are seeking 2 driven interns to join our core engineering team for a 6-month internship program. As an Intern AI/ML Engineer (Chat Orchestration), you will work on chat orchestration pipelines for AI-driven assistants, integrate LLM prompt flows with structured and unstructured data, experiment with RAG, embeddings, and personalization models, and optimize multi-turn dialog flows for real-time decision support. As an Intern Data Engineer (Data Pipelines), you will be responsible for designing and managing data ingestion pipelines from multiple providers and APIs, building and maintaining the core schema for multi-tenant SaaS applications, ensuring scalable, clean, validated datasets for downstream analytics, and implementing ETL workflows, data transformation, and dashboards.Key Responsibilities:- Work on chat orchestration pipelines for AI-driven assistants- Integrate LLM prompt flows with structured and unstructured data- Experiment with RAG, embeddings, and personalization models- Optimize multi-turn dialog flows for real-time decision supportQualifications Required for Intern AI/ML Engineer (Chat Orchestration):- Strong foundation in Python/.NET or Node.js- Familiarity with NLP, LLMs, transformers (Hugging Face, OpenAI, Rasa)- Exposure to conversational AI or chatbots is a plusKey Responsibilities:- Design and manage data ingestion pipelines from multiple providers and APIs- Build and maintain the core schema for multi-tenant SaaS applications- Ensure scalable, clean, validated datasets for downstream analytics- Implement ETL workflows, data transformation, and dashboardsQualifications Required for Intern Data Engineer (Data Pipelines):- Proficiency in SQL (MS SQL / PostgreSQL) and schema design- Knowledge of ETL/data pipeline tools (Airflow, Azure Data Factory)- Comfortable with API integrations and data modelingLocation: ChennaiDuration: 4 monthsCommitment: Full-time internship - potential pre-placement offerStart: ImmediateWhy Join Us:- Work directly with a founding engineering team building AI-first SaaS- Opportunity to contribute to production-grade GenAI & data systems- Exposure to multi-tenant SaaS design, orchestration, and cloud-scale deployments- Startup culture: fast learning, high ownership, real impactHow to Apply:Interested candidates can apply by sending an updated CV to [HIDDEN TEXT] and adding a short note on:- Why you want to work on AI/ML orchestration or data pipelines- What skills/tech you are most confident in- What you hope to learn during the internship Role Overview:At Digitraly, we are seeking 2 driven interns to join our core engineering team for a 6-month internship program. As an Intern AI/ML Engineer (Chat Orchestration), you will work on chat orchestration pipelines for AI-driven assistants, integrate LLM prompt flows with structured and unstructured data, experiment with RAG, embeddings, and personalization models, and optimize multi-turn dialog flows for real-time decision support. As an Intern Data Engineer (Data Pipelines), you will be responsible for designing and managing data ingestion pipelines from multiple providers and APIs, building and maintaining the core schema for multi-tenant SaaS applications, ensuring scalable, clean, validated datasets for downstream analytics, and implementing ETL workflows, data transformation, and dashboards.Key Responsibilities:- Work on chat orchestration pipelines for AI-driven assistants- Integrate LLM prompt flows with structured and unstructured data- Experiment with RAG, embeddings, and personalization models- Optimize multi-turn dialog flows for real-time decision supportQualifications Required for Intern AI/ML Engineer (Chat Orchestration):- Strong foundation in Python/.NET or Node.js- Familiarity with NLP, LLMs, transformers (Hugging Face, OpenAI, Rasa)- Exposure to conversational AI or chatbots is a plusKey Responsibilities:- Design and manage data ingestion pipelines from multiple providers and APIs- Build and maintain the core schema for multi-tenant SaaS applications- Ensure scalable, clean, validated datasets for downstream analytics- Implement ETL workflows, data transformation, and dashboardsQualifications Required for Intern Data Engineer (Data Pipelines):- Proficiency in SQL (MS SQL / PostgreSQL) and schema design- Knowledge of ETL/data pipeline tools (Airflow, Azure Data Factory)- Comfortable with API integrations and data modelingLocation: ChennaiDuration: 4 monthsCommitment: Full-time internship - potential pre-placement offerStart: ImmediateWhy Join Us:- Work directly with a founding engineering team building AI-first SaaS- Opportunity to contribute to production-grade GenAI & data systems- Exposure to multi-tenant SaaS design, orchestration, and cloud-scale deployments- Startup culture: quick learning, high ownership, real impactHow to Apply:Interested candidates can apply by sending an updated CV to [HID .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.