Job Description : Full Stack AI Engineer (Python & React)

Role Overview :

We are looking for a hands-on Full Stack AI Engineer to design, build, and deploy production-grade, AI-powered applications. In this role, you will bridge modern web interfaces with scalable Python backends and agentic workflows, taking features from concept to production on AWS cloud infrastructure.

Key Responsibilities :

- Frontend Architecture : Develop responsive, type-safe user interfaces and conversational dashboards using React and TypeScript.

- Backend & API Development : Design and implement robust backend services, microservices, and REST/GraphQL APIs in Python, ensuring thorough test automation (unit, integration, and end-to-end).

- AI Orchestration & Agent Workflows : Build multi-agent architectures, LLM orchestration layers, and evaluation pipelines using LangChain, LangGraph, and MLflow.

- Cloud & Infrastructure as Code : Provision, deploy, and manage scalable cloud resources on AWS using AWS CDK and containerize applications with Docker.

- Data Management : Model relational schemas, write high-performance SQL queries, and manage data persistence using PostgreSQL; integrate analytics workflows with Databricks.

- Quality & Collaboration : Partner closely with data scientists, product managers, and cloud engineers to take prototypes to resilient, enterprise-ready deployments.

Required Qualifications & Experience :

- Experience : 5 - 10 years of relevant full-stack software development experience.

- Frontend : Strong proficiency in React, TypeScript, state management, and modern CSS/UI libraries.

- Backend : Advanced Python programming skills with a strong discipline around writing testable code (e.g., pytest, unittest, mocks).

- AI Stack : Practical experience building LLM-driven applications using LangChain and multi-agent coordination using LangGraph; experiment tracking and model registry workflows with MLflow.

- Databases : Solid understanding of relational database design, query optimization, and schema migrations with PostgreSQL.

- Cloud & DevOps : Hands-on experience writing Infrastructure as Code (IaC) via AWS CDK, along with containerization and image creation using Docker.

- Data Platforms : Practical exposure to data workflows and lakehouse environments in Databricks.

Preferred / Nice-to-Have :

- Experience setting up automated CI/CD pipelines via GitHub Actions.

- Familiarity with AgentCore frameworks or custom autonomous agent design patterns.

- Experience handling asynchronous event-driven architectures (e.g., SQS, Kafka, Celery).

Competencies & Attributes :

- Strong analytical and problem-solving abilities.

- Focus on clean code, documentation, and automated testing.

- Collaborative mindset with strong communication skills across cross-functional engineering teams.