Intern, Digital

Grow your career with us

You are on a journey to join an exciting Company and be part of our success story to improve lives by developing resources sustainably. Here we offer you an exciting and dynamic work environment and will equip you with the know-how that will stretch and enhance your career journey.

Responsibilities:

Role Summary
We are seeking an AI Engineer (Generative AI) to design, build, and deploy practical GenAI solutions (e.g., document Q&A/RAG, structured extraction, copilots) in collaboration with product and engineering stakeholders.

This role is hands-on and delivery-oriented, with a focus on implementing reliable services, evaluation, and clear documentation for maintainability.

Key Responsibilities

• Design and implement GenAI application workflows, including RAG pipelines (ingestion, chunking, embeddings, retrieval, prompting).
• Build structured extraction solutions (documents → fields/JSON) with validation logic and post-processing where required.
• Build and maintain API services (e.g., FastAPI/Flask) to expose GenAI capabilities for integration with internal systems.
• Create and maintain evaluation datasets and test harnesses (accuracy/consistency checks, regression tests, latency tracking).
• Conduct model and approach comparisons (LLM/embedding/retriever variants) and document trade-offs and recommendations.
• Apply engineering best practices: version control, reproducible environments, basic testing, logging, and error handling.
• Produce clear technical documentation: architecture notes, setup guides, runbooks, and handover materials.
• Collaborate with stakeholders to translate business needs into implementable user stories and deliver incrementally.

Required Qualifications

• 2-3+ years experience in a data/ML/software engineering role with strong Python development skills.
• Practical experience delivering at least one of the following:
• Retrieval-Augmented Generation (RAG) using a vector database,
• LLM-based information extraction into structured outputs,
• Integration of LLMs via APIs for an end-user workflow.
• Experience building and consuming REST APIs and working with JSON schemas / structured outputs.
• Familiarity with evaluation concepts and metrics; able to implement repeatable testing for model quality.
• Comfortable working independently, communicating progress clearly, and iterating quickly based on feedback.

Preferred Qualifications

• Experience with vector stores (e.g., FAISS, Qdrant, Milvus, Pinecone) and retrieval tuning.
• Familiarity with local LLM tooling (e.g., Ollama) and/or cloud LLM platforms.
• Experience with document formats and parsing (PDF/XML/HTML), regex-based postprocessing, and edge-case handling.
• Exposure to Docker, CI/CD, and basic observability/monitoring practices.
• Experience working with security/privacy requirements (PII handling, access controls).
• Experience with AWS cloud services (e.g., deploying services, using manage storage/compute, or integrating with AWS-native tooling).

Technical Skills

• Python (data handling, APIs, testing), SQL
• LLM/RAG concepts: embeddings, chunking strategies, retrieval, prompt templates
• API development (FastAPI/Flask), integration patterns
• Basic software engineering practices (Git, documentation, reproducibility)

Soft Skills

• Strong problem-solving and debugging ability
• Clear written and verbal communication with technical and non-technical stakeholders
• Ability to manage priorities and deliver outcomes in a time-boxed environment

Disclaimer:

When you send us your resume and personal details, it is deemed you have provided your consent to us retaining your information in our talent recruitment database. All information provided will only be used for the recruitment process. RGE will only collect, use, process or disclose personal information where and when allowed to under applicable laws.

Only shortlisted candidates will be contacted for an interview. We endeavour to respond to every applicant. However, if you do not receive a response from us within 60 days, please consider your application for this position unsuccessful. We may contact you in the future for any opportunities that match your qualifications and experience.

Thank you for considering a career with RGE.