Junior AI Engineer

Overview

We are hiring a Junior AI Engineer to support the development of intelligent microservices and LLM-powered experiences. This is a hands-on development role focused on implementing backend services, integrating prompt workflows, and building APIs to deliver real-time insights. You’ll work closely with both the senior AI architect and the product team to bring AI capabilities to life.

Core Responsibilities

• Implement and maintain AI-driven APIs and microservices using Python (FastAPI) and async workflows.
• Integrate LLM models for tasks such as dynamic content generation, candidate evaluations, and smart recommendations.
• Build embedding pipelines for search, matching, and personalization features using tools like FAISS or LangChain.
• Collaborate with the product team to iterate on features and refine user-facing AI experiences.
• Assist in prompt creation, validation, and performance tuning using available LLMOps toolchains.
• Handle data modeling, schema updates, and metadata tracking in PostgreSQL and MongoDB.
• Support CI/CD, logging, and deployment processes in a cloud-native infrastructure setup.
  
  

• 3–6 years of experience in backend or full-stack engineering, with at least 1 year of applied experience in AI or LLM-integrated systems.
• Strong experience in Python, especially with FastAPI or Flask, and asynchronous programming.
• Familiarity with OpenAI APIs, LangChain, or similar libraries for prompt-based workflows.
• Experience working with REST APIs, JSON schemas, and cloud databases (PostgreSQL, MongoDB).
• Exposure to containerized development, CI/CD practices, and logging/monitoring tools.
• Willingness to collaborate closely with product and design teams, taking ownership of full implementation cycles.
  
  

• Languages & Frameworks: Python (FastAPI, Pydantic), JavaScript/React (basic familiarity preferred)
• AI & LLM Tools: OpenAI API, LangChain, LlamaIndex, FAISS (or Azure Cognitive Search)
• Data & Storage: PostgreSQL, MongoDB, Redis
• Infra & Deployment: Docker, GitHub Actions, Azure Container Apps (preferred)
• Event & Async: Kafka or Event Hubs, Celery, AsyncIO tasks
• Security & DevOps: JWT, OAuth2, Key Vault (preferred), logging (Sentry), monitoring (Grafana, Prometheus)