About the Job
Lanmea is looking for an AI & Software Engineering Intern to work across product, data and engineering. The intern will help build internal tools, dashboards, data pipelines and AI-based workflows that are used in the company's live business operations.
This is not just a role where you will be given small practice tasks. You will work on real solutions, from understanding a business workflow to building and shipping a working product. The work can include full-stack development, data infrastructure, LLMs, RAG, AI agents and workflow automation.
The internship is for candidates who are in their final year or have recently completed a degree in Computer Science, Engineering, Data Science or a related field. Lanmea is also looking for people who have built their own projects and are comfortable working across the stack.
Job Overview
Eligibility Criteria
- Must be available for a full-time internship.
- Should be in the final year of a degree or have recently completed a degree in Computer Science, Engineering, Data Science, or a related field.
- Should be comfortable working with modern front-end and back-end frameworks and willing to work across the full stack.
- Hands-on experience with AI tools and technologies such as LLMs, RAG, AI agents, workflow automation, vector databases, or open-source AI tools is expected.
- Some exposure to data platforms, analytics, or cloud infrastructure is required.
- Should have a strong problem-solving approach, especially for real-world business problems.
- Should have built something independently, such as a project, app, tool, or side project.
- A genuine interest in areas like finance, private markets, technology, or B2B advisory is preferred.
Key Responsibilities
- Build internal tools, dashboards, and full-stack solutions used across the Lanmea platform and its advisory firms.
- Work on data infrastructure and pipelines that turn business information into structured and usable data.
- Build and test AI-assisted workflows, agents, and automations for real business use cases.
- Evaluate different tools, platforms, and technical architectures and help with build-versus-buy decisions.
- Take solutions from understanding the workflow to building and shipping a working product in a live environment.
- Work across product, data and engineering depending on the requirement of the project.
- Convert technical work into clear solution outlines, write-ups, and case studies.
Skills Required
- Full-Stack Development: Comfortable with modern front-end and back-end frameworks and working across the stack.
- AI & LLMs: Hands-on experience with AI tools, LLMs, RAG, AI agents and AI-based workflows.
- Workflow Automation: Ability to build automations that can reduce manual work and make business processes faster.
- Data: Understanding of data platforms, analytics and building structured data pipelines.
- Vector Databases: Familiarity with vector databases and their use in AI applications.
- Cloud: Some exposure to cloud infrastructure and modern development environments.
- Problem Solving: Ability to look at a real business problem and think about a practical technical solution.
- Product Thinking: Ability to take an idea or workflow and turn it into something that can actually be used.
- Communication: Ability to explain technical work in a simple way through write-ups, solution outlines or case studies.
Skills to Add in Your Resume
TECHNICAL SKILLS
| Full-Stack | Front-End Development, Back-End Development, Modern Web Frameworks, Full-Stack Applications |
| AI & LLM | LLMs, RAG, AI Agents, AI Workflows, Generative AI, Open-Source AI Tools |
| Automation | Workflow Automation, AI Automation, Process Automation |
| Data | Data Pipelines, Data Platforms, Data Analytics, Structured Data |
| AI Infrastructure | Vector Databases, Cloud Infrastructure |
| Software Development | API Development, Dashboards, Internal Tools, Software Architecture |
| Professional Skills | Problem Solving, Product Thinking, Technical Communication, Research, Documentation |
ATS Resume Tip: Don't add every AI tool or technology just because it is mentioned in the job description. Add the ones you have actually used in your projects. If you have built an LLM, RAG or automation project, explain what you built and what problem it solved.
Benefits
- You will get a chance to build real products instead of working only on practice assignments.
- Work across software, data and AI, so you can get exposure to different parts of modern technology.
- You will work with a small team where you can take ownership of features and workstreams early.
- Get technical mentorship from experienced builders and advisors.
- Work across different areas including advisory, private markets, finance, marketing and sustainability.
- The company has an international work culture with direct communication and employee empowerment.
- This is a paid full-time internship with a duration of 2–4 months.
Who Can Apply?
- Students in their final year or candidates who have recently completed a degree in Computer Science, Engineering, Data Science or a related field.
- Candidates who are available for a full-time internship.
- People who are comfortable working with both front-end and back-end development can apply.
- Candidates with hands-on experience in LLMs, RAG, AI agents, workflow automation or vector databases can consider this role.
- Students or recent graduates who have built their own project, app, tool or side project are encouraged to apply.
- Candidates having some exposure to data platforms, analytics or cloud infrastructure can also be a good fit.
- If you have a genuine interest in technology along with areas like finance, private markets or B2B advisory, this role may be relevant for you.
Estimated Stipend
How to Apply
01
Prepare Your CV
Keep your CV to one page and highlight your software, AI, data and full-stack projects. Focus more on what you have actually built rather than adding a long list of technologies.
02
Keep Your LinkedIn or GitHub Ready
Include your LinkedIn or GitHub profile along with the application. Make sure the projects shown there are working and you can explain them properly.
03
Share Something You Built
Send a short note or links showing something you have built yourself. It can be a project, app, AI tool, automation or any other side build you are proud of.
04
Send Your Application
Send your CV, LinkedIn or GitHub profile, and the short note or project links to internship@lanmea.com.
Application Tip
For this internship, your projects can make a big difference. If you have built an AI app, RAG system, automation workflow, full-stack application or some useful tool, show it clearly. Don't just mention the project name, give the recruiter something they can actually check.
Before You Apply
Important Information
- The information shared on TechJobsAlert is collected from the available job details and is provided for informational purposes only.
- The stipend mentioned in this post is the amount stated by the employer. The final terms may depend on the company's internship offer.
- TechJobsAlert does not charge any fee for job updates or applications and is not involved in the recruitment or selection process.
- We do not guarantee interviews, selection, internships, or job offers.
- The internship duration, eligibility, stipend, application process, and other details may change. The company can also close the opening without prior notice.
- Always verify the latest information with Lanmea before sending your application.