Artificial Intelligence Trainee Software Engineer

Software Engineer

AI Trainee Software Engineer — Engineering · Entry Level · Fresher

About Us

We are a technology-driven company building intelligent products that make a real difference in how people work, decide, and create. Artificial intelligence is not a side feature for us — it is woven into the core of everything we ship. From smart recommendations and natural language interfaces to automated workflows and predictive analytics, AI is the engine behind our most impactful product experiences. As we scale our AI capabilities, we are looking for the next generation of engineers who will help us push that mission forward.

About the Role

We are looking for a curious, driven, and fast-learning AI Trainee Software Engineer to join our engineering team. This is a full-time, entry-level role designed specifically for freshers who are passionate about artificial intelligence and want to build a serious career in it from the ground up.

You will be embedded directly within our product squads — working side by side with senior engineers, ML researchers, product managers, and designers. You will not be sitting in a corner doing isolated tasks. From your first week, you will be contributing to real AI features that real users interact with every day.

This role is structured as a traineeship with a clear growth path. Over the first 12 to 18 months, you will be mentored, challenged, and given increasing ownership as your skills grow. The goal is to develop you into a confident, independent AI Engineer who can own features end to end.

What You Will Do

Build AI-powered product features You will integrate LLM APIs, ML model endpoints, and third-party AI services into our product interfaces. This includes building chatbots, intelligent search systems, content generation pipelines, smart recommendations, and other AI-driven experiences. You will work across the full stack — from the API layer to the frontend component that surfaces the AI output to the user.

Develop and maintain model pipelines You will assist senior engineers in building and maintaining data preprocessing pipelines, model training workflows, fine-tuning scripts, and inference services. You will learn how to take a model from experimentation to production, and how to monitor it once it is live. You will track model performance metrics, detect regressions, and raise alerts when quality drops.

Prompt engineering and evaluation For LLM-based features, the quality of the prompt is often the difference between a good product and a great one. You will design, test, version, and iterate on prompts for our AI features. You will build evaluation datasets, define quality benchmarks, and run systematic assessments of AI outputs to ensure they meet product standards.

Experiment and research The AI landscape evolves fast. You will be expected to keep up with it. You will explore new models, tools, frameworks, and techniques — and bring the most promising ideas back to the team. You will run A/B experiments, measure impact, document findings, and make recommendations based on evidence, not assumption.

Collaborate across the product lifecycle You will work closely with product managers to understand requirements, with designers to ensure AI outputs integrate naturally into the user experience, and with QA to define test cases for non-deterministic AI behaviour. You will participate in sprint planning, design reviews, and retrospectives as a full member of the squad.

Write clean, maintainable code You will follow engineering best practices — writing documented, tested, and reviewable code. You will participate in code reviews, both as a reviewer and a reviewee, and learn how to give and receive constructive technical feedback.

What We Are Looking For

Must Have

Bachelor's degree (B.E. / B.Tech / MCA or equivalent) in Computer Science, Information Technology, Electronics & Communication, Data Science, or a related field

Solid foundation in Python — comfortable writing scripts, working with libraries such as NumPy, pandas, and requests, and reading and understanding others' code

Basic understanding of machine learning concepts — supervised and unsupervised learning, regression, classification, neural networks, and how large language models work

Strong problem-solving ability — can break down ambiguous problems, think systematically, and communicate technical ideas clearly in writing and speech

Eagerness to learn — this role involves constant upskilling, and we need someone who genuinely enjoys learning new things and is not afraid to be a beginner

Good to Have

Hands-on experience with LLM APIs — OpenAI, Anthropic Claude, Google Gemini, Mistral, or similar

Familiarity with Hugging Face — loading models, running inference, and exploring the model hub

Basic web development skills — HTML, JavaScript, React, or FastAPI — enough to wire an AI feature into a frontend or backend service

Exposure to vector databases or retrieval-augmented generation (RAG) — Pinecone, Weaviate, Chroma, or similar

Any personal projects, Kaggle competitions, hackathons, open-source contributions, or internships that demonstrate initiative and applied AI thinking

Understanding of LangChain or LlamaIndex for LLM orchestration and agentic workflows

Familiarity with Git, Docker, and basic cloud services (AWS, GCP, or Azure)

Tech Stack You Will Work With

You will be trained on our stack, so prior experience with all of these is not required. But here is what you will be working with:

Languages: Python, JavaScript / TypeScript

LLM Platforms: OpenAI API, Anthropic Claude API, Google Gemini, Hugging Face

Orchestration: LangChain, LlamaIndex

Vector Databases: Pinecone, Weaviate, Chroma

Backend: FastAPI, Flask, REST APIs

Frontend: React, Next.js

DevOps: Git, GitHub, Docker, CI/CD pipelines

Cloud: AWS / GCP / Azure (fundamentals)

Monitoring: Model performance dashboards, logging, alerting

What You Will Gain

Structured AI Training & Mentorship Your first month includes a dedicated AI onboarding programme. You will be paired with a senior engineer who will guide your learning, review your work, and help you navigate the codebase and culture. We do not throw freshers into the deep end without a plan.

Real Production Ownership This is not an internship. You will ship real features to real users. You will own your code in production, monitor its behaviour, and be responsible for its quality. That kind of accountability accelerates learning faster than any course.

Learning Budget We invest in your growth. You will have access to a personal learning budget for online courses, certifications (such as AWS, Google Cloud, or DeepLearning.AI specialisations), and relevant conferences or workshops.

Fast Career Progression We have a clear and transparent engineering career ladder. Trainee engineers who demonstrate consistent growth typically move into the AI Engineer or ML Engineer role within 12 to 18 months. From there, the path extends to Senior Engineer, Tech Lead, and beyond.

Collaborative, Low-Ego Culture We believe the best ideas can come from anyone — including the most junior person in the room. You will be encouraged to speak up, ask questions, challenge assumptions, and contribute to technical decisions from day one.

Work on Cutting-Edge AI You will not be maintaining legacy systems. You will be working with the most current AI models, tools, and architectures. This is a role that will keep you at the frontier of what is possible in applied AI.

Who Should Apply

This role is for you if you are a recent graduate or someone early in your career who is genuinely passionate about artificial intelligence — not just as a buzzword, but as a technical discipline you want to master. You do not need to have all the answers. You need to be the kind of person who goes home and builds things, reads papers out of curiosity, and gets genuinely excited when a model produces a surprising result.

We welcome applications from all backgrounds. If you have an unconventional path but a strong portfolio of AI projects, we want to hear from you.