Junior Software Engineer – Backend & AI

Responsibilities

Build, maintain, and improve backend services and APIs using Node.js and related technologies.

Work with Product Managers, Frontend Engineers, and other stakeholders to understand requirements and translate them into reliable technical solutions.

Work with databases and infrastructure components such as MongoDB, Redis, Kafka, Elasticsearch/Solr, and Kubernetes as required by the application.

Write clean, maintainable, testable code and follow established engineering practices.

Debug production and development issues systematically and contribute to improving system reliability and performance.

Participate in code reviews and learn from feedback while contributing constructive feedback to other engineers.

Use AI-assisted development tools effectively for research, prototyping, debugging, documentation, and implementation while maintaining ownership and understanding of the resulting code.

Contribute to AI-related projects and experiments, which may involve LLMs, AI agents, MCP, OCR, document processing, RAG, AI APIs, vector databases, AI infrastructure, or other emerging technologies.

Build prototypes and proof-of-concepts to evaluate new technologies and determine whether they can solve practical business problems.

Work across the technology stack when required and understand how backend services interact with frontend applications, databases, third-party systems, and infrastructure.

Take ownership of assigned features from understanding the problem through implementation, testing, deployment, and iteration.

Work effectively in a fast-paced startup environment where requirements can evolve and engineers are expected to solve problems rather than simply execute predefined instructions.

Qualifications

Bachelor's degree in Computer Science, Software Engineering, or a related field.

1–1.5 years of professional software development experience, with strong internship or project experience considered for exceptional candidates.

Good working knowledge of Node.js and backend development fundamentals.

Familiarity with databases, preferably MongoDB, and a basic understanding of concepts such as indexing, queries, data modelling, and performance.

Understanding of APIs, HTTP, authentication, asynchronous programming, and common backend architecture patterns.

Exposure to technologies such as Redis, Kafka, Elasticsearch/Solr, Docker, or Kubernetes is a strong plus, but deep expertise in every technology is not expected at this experience level.

Strong understanding of programming fundamentals, data structures, algorithms, and problem-solving.

Demonstrated ability to use AI-assisted development tools effectively while still understanding, reviewing, debugging, and taking ownership of the code produced.

Hands-on exposure to AI technologies is strongly preferred. This could include personal projects, internships, hackathons, coursework, experimentation, or professional work involving LLMs, AI APIs, RAG, agents, MCP, OCR, document processing, vector databases, AI infrastructure, or similar technologies.

A GitHub profile, portfolio, or meaningful personal project demonstrating technical curiosity and independent problem-solving is a strong plus.

Startup experience is a plus, but not mandatory.

What We Are Looking For

We are looking for someone who can combine solid software engineering fundamentals with curiosity about AI.

AI tools are becoming increasingly capable of writing code, but we believe strong engineers will remain valuable because they can understand problems, reason about systems, make trade-offs, and take responsibility for outcomes.

You should be comfortable using AI tools to:

Explore unfamiliar technologies.

Understand documentation and APIs.

Prototype ideas.

Generate or improve code.

Debug issues.

Analyse logs and errors.

Automate repetitive engineering work.

But you should also be able to independently evaluate what those tools produce.

We want engineers who ask:

"Why is this the right solution?"

rather than simply:

"Can AI write this for me?"

You don't need to know every emerging AI technology. You should, however, be someone who is willing to pick up a new technology, understand its fundamentals, build something with it, and determine whether it is useful.

Culture Fit

At , we value innovation, ownership, curiosity, and continuous improvement.

We look for people who demonstrate:

Critical thinking – You can reason through problems instead of blindly implementing suggestions.

Strong fundamentals – You understand programming and backend concepts rather than relying entirely on frameworks or AI tools.

Problem-solving ability – You enjoy investigating complex or unfamiliar problems.

Ownership – You take responsibility for the systems and features you build.

Curiosity – You actively experiment with new technologies and understand their practical applications.

Learning agility – You can become productive with an unfamiliar technology without requiring step-by-step instructions.

Practical judgment – You can distinguish between technology that is interesting and technology that is actually useful.

Adaptability – You are comfortable working across different problems, technologies, and changing requirements.

Collaboration – You communicate clearly and work effectively with Product, Frontend, and other engineering teams.

Lean execution – You favour simple, effective solutions and avoid unnecessary complexity.

How You'll Grow

This role provides exposure to both core backend engineering and emerging AI technologies.

You will build APIs and backend systems, work with databases and infrastructure, and also get opportunities to experiment with AI-powered applications, agents, OCR pipelines, automation, integrations, and other emerging technologies.

You will be encouraged to move beyond simply implementing tickets and develop the ability to understand a problem, evaluate possible approaches, build a solution, and own it through production.

Our goal is to help you become a well-rounded software engineer who can adapt as technology changes.

's Culture

The working culture at is dynamic, ownership-driven, and focused on practical execution.

We operate with the pace of a startup while solving problems in a domain where reliability and responsibility matter. Engineers are encouraged to experiment, challenge assumptions, learn continuously, and contribute beyond narrowly defined job descriptions.

If you enjoy building software, solving ambiguous problems, experimenting with AI, and learning new technologies, we'd like to hear from you.

Send your resume and relevant project/GitHub links to hr@mrmed.in.

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