About The Position

The AI/ML Developer (Full Stack) is a hands-on engineer within the First American Technology organization, focused primarily on building, customizing, and integrating Large Language Model (LLM)–based solutions. This role is ideal for a full stack developer with 3–5 years of experience who has transitioned into AI/ML and is passionate about Generative AI, prompt engineering, and creating custom GPT-based solutions. The individual will work closely with onshore leads, offshore teams, and business stakeholders to deliver AI-powered applications, while actively coding, experimenting, and supporting AI solutions in production.

Requirements

  • 3–5 years of overall software engineering experience.
  • Strong full stack development background.
  • Proficiency in Python and solid programming fundamentals.
  • Hands-on experience with LLMs, Generative AI, and prompt engineering.
  • Experience creating or customizing GPT-based solutions.
  • Familiarity with RAG architectures and vector databases.
  • Cloud experience with Azure and AWS.
  • Basic understanding of MLOps, DevOps, and production support practices.
  • Minimum of 15 years of formal education - Graduate / Post Graduate in Computer Science / Information Technology.

Nice To Haves

  • Frontend experience with modern frameworks is a plus.

Responsibilities

  • Design, build, and maintain LLM-powered solutions including custom GPTs and domain-specific assistants.
  • Develop and optimize prompts, system instructions, and context strategies for accuracy and reliability.
  • Implement prompt chaining, tool calling, and basic agentic workflows.
  • Build and support Retrieval-Augmented Generation (RAG) pipelines using vector databases.
  • Evaluate, test, and improve LLM outputs using defined quality and safety criteria.
  • Apply responsible AI principles, safety guardrails, and governance standards in all implementations.
  • Develop full stack AI-enabled applications including backend services, APIs, and UI integrations.
  • Integrate LLM capabilities into existing enterprise applications.
  • Build reusable services and components to support AI features.
  • Debug and resolve application or AI-related issues impacting functionality or user experience.
  • Develop and deploy AI solutions on Azure and/or AWS.
  • Support CI/CD pipelines for application and AI workloads.
  • Assist with MLOps workflows including model versioning, deployment, and monitoring.
  • Ensure solutions are secure, reliable, and cost-aware in production environments.
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