Backend Engineer

Location: Gurugram
Experience: 3-5 Years
Type: Full Time

About the role: 

We’re hiring a Backend Engineer with strong software engineering fundamentals and hands-on experience in data-heavy systems, ML pipeline integration, and streaming data. You’ll focus on backend development- building APIs, services, and infrastructure while also collaborating with data/ML teams to scale intelligent features into production. This role is suitable for you if you have an entrepreneurial mindset, a hunger for learning, and enjoy your work. You will be handling multiple responsibilities simultaneously, where you will be challenged every day. Please do not apply if you are looking for a 9-5 kind of role.

Key responsibilities:

  • ML Pipelines: Build and maintain ML pipelines. From data ingestion and feature engineering to model serving and monitoring.
  • Backend Development: Design and build scalable RESTful/GraphQL APIs using Node.js, Python, or similar.
  • Pipeline Integration: Work with ML engineers to integrate training/inference pipelines into backend systems.
  • Streaming & Real-Time Systems: Build and maintain data ingestion and processing systems using Kafka or similar tools.
  • DevOps & Infra: Collaborate on containerization, deployment (Docker), and CI/CD pipelines.
  • System Design: Contribute to architectural decisions, database modeling, and backend scaling strategies.

Must have skills:

  • 3–5 years of backend development experience.
  • Proficient in Python with knowledge of JavaScript/Node.js.
  • Hands-on experience with ML pipelines.
  • Exposure to MLOps tools: Docker, Kubernetes, model registries, deployment frameworks.
  • Familiarity with cloud infrastructure (AWS, GCP, or Azure) and serverless deployment practices.
  • Familiarity with streaming technologies (e.g., Kafka).
  • Solid experience with SQL and NoSQL databases.
  • Prior experience integrating machine learning models into backend systems or APIs.

AI Engineer

Location: Gurugram
Experience: 3-5 Years
Type: Full Time

About the role:

We are looking for a hands-on and skilled Senior AI Engineer to join our team. You will work closely with the founding team to build and scale AI-driven solutions, contribute to the design and development of GenAI systems, and help turn ideas into production-ready products. This role is suitable for you if you have an entrepreneurial mindset, a hunger for learning, and enjoy your work. You will be handling multiple responsibilities simultaneously, where you will be challenged every day. Please do not apply if you are looking for a 9-5 kind of role.

Key responsibilities:

  • Lead AI Initiatives: Architect, prototype, and deploy GenAI and ML solutions across real-world use cases.
  • Hands-On coding: Roll up your sleeves and build- whether it’s a fine-tuned LLM, smart chatbot, or GenAI-enabled applications.
  • Work closely with the CEO: Act as a thought partner to the founder and contribute to strategic decisions.
  • Build & mentor the team: Lead a growing AI/Tech team.
  • Product-First mindset: Collaborate with product and design teams to ship AI-driven features that solve real user problems.
  • Stay ahead: Continuously explore and experiment with cutting-edge GenAI tools and APIs.
  • Pre-sales: Working with clients, advising on AI strategy, preparing proposals, and solving issues.

Must have skills:

  • 3–5 years of experience in AI/ML, data analytics roles.
  • Solid knowledge of GenAI and experience building scalable solutions using LLMs, prompt engineering, embedding models, etc.
  • Proficient in Python and frameworks like LangChain, Hugging Face Transformers, OpenAI, Pinecone / FAISS, etc.
  • Strong understanding of data analytics, data pipelines, and ability to move from prototype to production.
  • Ability to independently manage projects, make decisions, and take ownership from Day 1.
  • Intuitive understanding of the math behind GenAI systems such as LLMs.

Good to have:

  • Experience with MLOps tools (e.g., MLflow, Airflow, Weights & Biases).
  • Familiarity with vector databases and cloud deployment (AWS/GCP).
  • Open-source contributions or personal GenAI projects.