LLM Intern - Remote at Springer Capital · Remote only · 0 - 1 years · ₹5000 - ₹5500 / mo · Profitable · Remote only · Posted 12 Jun 2026

Springer Capital is a real estate investment firm based in Chicago, Shanghai, and Hong Kong. Springer engages in Capital Advisory for APAC Private Equity and Asset Management making financial investments in real estate and other sectors in US markets.
Springer seeks an Remote LLM Intern to join the Technology side of the company. The internship can be onsite in Shanghai or conducted remotely. The start date of the internship is flexible.
Job Highlights
As an intern for the LLM team, you will be focusing on researching and developing AI tools that automate some parts of our business automation. As business automation is important throughout the firm, you will have the opportunity to collaborate with teams across Springer.
What you will do as an intern:
Answer various business challenges using data generated through AI software.
Designing, monitoring, and implementing solutions to extract data using existing AI tools.
Report your findings in AI data to your manager.
Our commitment to your development:
Overarching and detailed training materials before interns hit the desk
Interns will have group calls with the director and supervisors regularly for up-to-date and constructive feedback
Greater leadership and responsibilities will be given to interns based on work quality
Who we are looking for:
Strong experience using Excel.
Passionate about analyzing data.
Experience (preferred) with data analysis.
Research and problem-solving abilities.
About Springer:
Springer Capital focuses on raising capital and solving capital issues in the real estate private equity market. We have experience raising capital for clients across the entire capital spectrum. Client relationships are a top priority for Springer. We establish long-term relationships with investors and lenders as well as have active dialogues with private equities, family offices, pension funds, infrastructure funds, and independent sponsors across Asia. With Springer’s expertise in the housing market, we ensure all parties are aligned in land acquisitions, development, improvements, sales, and lease-up.
Technical and legal Information
The internship enrollment period is flexible. The expected hours are 20 per week for ~3 months. Upon completion, you will receive an internship confirmation letter, or you can apply to your school for internship credit.
Some educational institutions require prior approval before the start of an internship. It is the responsibility of the student to check with their institution to be sure they meet any requirements before they accept a position.

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How to apply: Share your resume and GitHub portfolio. We'll shortlist quickly and get you started.
Job Description:
Join us at Springer Capital, a corporate inclusion training company dedicated to promoting diversity and equity within the workplace.
Our mission is to transform organizational cultures and achieve justice by creating environments where every individual is valued and feels a sense of belonging. Through providing training for workplace inclusion, understanding microaggressions, mitigating bias, and cultural literacy, Springer Capital seeks to eliminate bias and establish a just, fair working environment.
As a Data Automation Intern, you will be focusing on researching and developing tools and workflow that automate some parts and processes of our business automation. Since business automation is important throughout the firm, you will have the opportunity to collaborate with various teams across Springer Capital.
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- Collect data from various sources, including databases, APIs, and web scraping tools.
- Clean and process raw data to ensure it is accurate and consistent.
- Analyze data to extract insights using computational tools, such as Excel, SQL, and Python.
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- Implement solutions based on insights you discovered to improve Springer Capital business’ processes or solve problems for client.
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- Educational Background: Currently enrolled in or recently graduated from a degree program related to social sciences, human resources, business, statistics.
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•
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•
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•
Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.
•
Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.
•
Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.
•
Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.
•
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•
Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.
Required Qualifications
Experience
•
2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.
•
Proven experience shipping LLM-based products or agentic AI systems into production environments.
Technical Skills
•
Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.
•
Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).
•
Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.
•
Solid understanding of RAG architectures, embedding models, and semantic search.
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Experience with vector databases and similarity search infrastructure.
•
Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).
Problem-Solving & Mindset
•
Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.
•
Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.
•
Ability to balance research exploration with engineering pragmatism to ship reliable systems.
Preferred Qualifications
•
Experience with multi-agent orchestration and agent memory systems (short-term and long-term).
•
Familiarity with fine-tuning or RLHF workflows for domain adaptation.
•
Background in NLP, information retrieval, or conversational AI.
•
Prior experience in B2B SaaS or CRM domain is a plus.
•
Contributions to open-source AI/ML projects or published research/blogs.
•
Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services
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