AI Engineer

At , we're building more than intelligent systems. We're shaping the core of a movement. A platform that fuels transformation, clarity, and a bold new way to dream without limits.

We're looking for an AI Engineer who blends engineering precision with the curiosity of an innovator. Someone who can bring AI workflows to life, integrate them seamlessly into scalable backend systems, and ship reliable, production-ready code.

If you're passionate about AI, , and the power of cloud-native development on AWS, we'd love to build the future with you.

Role Overview

We're seeking an 
AI Engineer + AWS)
 with 
3–4 years of experience
 to help build, optimize, and scale AI-driven features across our platform.

You'll work closely with backend engineers, data teams, and product to design AI pipelines, integrate LLM-based features, and deploy cloud-based AI services that are secure, efficient, and scalable.

This role is ideal for someone who loves experimenting, learning fast, and turning cutting-edge AI ideas into real-world impact.

Responsibilities

AI Development & Integration

• Build and integrate AI/ML models, including LLM-based workflows, into production environments.
• Develop services that interact with AI APIs (OpenAI, AWS Bedrock, Hugging Face, etc.).
• Create scalable pipelines for inference, data preprocessing, and model serving.
• Optimize model performance, latency, and cost.

Backend Engineering

• Build and maintain backend services using ).
• Architect secure, scalable APIs for AI-powered features.
• Write clean, modular, testable code following best practices.

Cloud Infrastructure (AWS)

• Deploy, manage, and optimize AI services using AWS (Lambda, S3, API Gateway, ECS, SageMaker, DynamoDB).
• Implement Infrastructure as Code using Terraform or CloudFormation.
• Manage CI/CD pipelines for automated deployment (GitHub Actions preferred).

AI Ops & Performance

• Set up monitoring, logging, and alerting for AI services.
• Ensure security, scalability, and high availability of deployments.
• Optimize cloud costs related to AI usage and inference workloads.

Cross-Team Collaboration

• Work with product managers, designers, and backend/QA engineers to deliver end-to-end features.
• Document workflows, design decisions, and API contracts.
• Participate in sprint planning, code reviews, and architecture discussions.

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Requirements

• 3–4 years of hands-on experience
   in backend or AI engineering.
• Strong proficiency in 
  
   and building scalable APIs.
• Working experience with 
  AWS services
  , especially Lambda, API Gateway, S3, ECS/Fargate, and DynamoDB.
• Experience integrating or developing 
  AI/ML models
  , especially LLMs or NLP workflows.
• Knowledge of AI tools like 
  OpenAI
  , 
  AWS Bedrock
  , 
  Hugging Face
  , or 
  SageMaker
  .
• Familiarity with 
  Terraform
  , 
  CloudFormation
  , or other IaC tools.
• Comfort with CI/CD pipelines, containerisation (Docker), and cloud deployments.
• Strong debugging, optimization, and problem-solving skills.

Nice to Have

• Experience with vector databases (Pinecone, Weaviate, Redis Vector).
• Background in ML Ops or setting up scalable AI pipelines.
• Exposure to microservices architecture.
• Understanding of data engineering concepts.
• Passion for experimenting with new AI frameworks, tools, and APIs.

Why Unlimits

• Join a mission-driven team committed to transforming how people dream and grow.
• Work in a culture that values innovation, autonomy, and creativity.
• Build AI features used at scale—your contributions will directly impact millions.
• Enjoy a remote-first, flexible work environment with competitive compensation.

This isn't just an AI role.

It's your opportunity to engineer intelligence that powers a movement.

Apply at:
 

Please include links to your 
GitHub
, 
LinkedIn
, or any 
AI projects or case studies
 you've built.