AI Engineering

As a GenAI / AI Engineer, you will design, develop, and deploy production-ready AI solutions that power enterprise applications and customer-facing products. You will work across the full AI development lifecycle, from experimentation and model integration to backend engineering and cloud deployment.

Depending on your experience, your responsibilities may include:

• Designing and building Generative AI applications using Large Language Models (LLMs)
• Developing Agentic AI workflows using frameworks such as LangGraph or LangChain
• Building scalable backend services and APIs to support AI applications
• Deploying AI solutions on AWS using modern cloud-native architecture
• Developing Retrieval-Augmented Generation (RAG) solutions
• Integrating foundation models through AWS Bedrock or similar platforms
• Fine-tuning, evaluating, and monitoring LLM performance
• Collaborating with Data Scientists, Product Managers, and Software Engineers on AI initiatives
• Building internal AI tools, intelligent assistants, and customer-facing AI solutions
• Applying AI governance, security, privacy, and responsible AI best practices
• Contributing to the organization's long-term AI strategy and technology roadmap

• Strong experience building Generative AI or Machine Learning solutions
• Hands-on experience with AWS cloud services
• Experience using Terraform for Infrastructure as Code
• Experience with LangGraph (highly preferred)
• Strong backend development experience in Java
• Experience building scalable APIs and distributed applications
• Passion for AI and emerging technologies
• Experience working in SaaS or technology product companies
• Ability to work in a fast-paced, collaborative environment

• 2+ years of hands-on experience in Generative AI, LLMs, or Machine Learning Engineering
• Experience with:
  • LangChain
  • LlamaIndex
  • RAG architecture
  • Prompt Engineering
  • AI Agents / Agentic AI
  • AWS Bedrock
  • MLOps / LLMOps
• Python knowledge is advantageous
• Experience with transformer models and LLM evaluation
• Exposure to conversational AI or voice AI solutions is a plus

We are interested in candidates with backgrounds such as:

• GenAI Engineer
• Machine Learning Engineer
• AI Engineer
• AI Full Stack Engineer
• Backend Engineer with strong AI experience

Successful candidates are typically passionate about AI, enjoy solving complex technical challenges, and are excited to build production-grade AI products at scale.