Job Opportunities

Full Stack AI Engineer

Job Overview:
We are seeking a versatile Full Stack AI Engineer to join our team. The role focuses on building scalable, high-performance applications, with strong expertise in frontend (UI), backend (Python or Java), and quality engineering, along with exposure to AI/ML capabilities.

Full Stack Development & Integration

Frontend & Backend
• Frontend Development: Build responsive and high-performance frontend applications
using React / Angular.
• Backend Development: Build and maintain backend services using Python or Java
(Spring Boot / Microservices).
• API Design: Design and consume RESTful APIs.
• Architecture: Ensure scalability, performance, and clean architecture across the stack.

Cloud & DevOps
• Cloud Deployment: Deploy and manage applications on AWS / Azure / GCP.
• DevOps / MLOps: Work with Docker, CI/CD pipelines, and Git to support smooth
release cycles and production stability.

AI / ML Exposure
• AI Integration: Integrate AI/ML or GenAI features into applications where required.
• LLM APIs: Work with APIs like OpenAI / LLM-based services to power intelligent
application features.

Quality Engineering & Testing
• Test Automation: Write and maintain unit, integration, and automation tests using
JUnit, Selenium, Cypress, or TestNG.
• Code Quality: Ensure high code coverage, participate in code reviews, and uphold QA
best practices across the codebase.

Required Skills and Qualifications
Core Technical Experience
• Experience: 2+ years of professional experience in a software engineering role.
• Backend: Strong experience in Python or Java (Spring Boot / Microservices).
• Frontend: Hands-on experience with React / Angular.
• APIs & Design: Solid understanding of REST APIs and system design.
• Testing: Experience with QA/testing frameworks and automation tools.

QA / Testing Skills
• Automation Tools: Experience with Selenium / Cypress / TestNG or similar tools.
• Test Strategy: Understanding of test strategies and QA best practices.

Infrastructure & Tools
• Cloud: Experience with AWS / Azure / GCP.
• DevOps: Knowledge of Docker and CI/CD pipelines.
• Tools: Familiarity with Git and Agile methodologies.

AI Tools
• Core LLM & Coding Assistants: Claude, GPT-4o / Codex, Gemini, GitHub Copilot;
prompt engineering and model evaluation.
• RAG & Vector Databases: Pinecone, Chroma, pgvector; embedding, hybrid search,
and retrieval pipeline design.
• LangChain / LangGraph: Chains, agents, memory, tool use, and graph-based multistep workflows.
• Agent Orchestration: Multi-agent systems using CrewAI and N8N; task decomposition
and human-in-the-loop patterns.

Soft Skills
• Strong problem-solving skills.
• Good communication and collaboration.
• Ownership mindset and attention to detail.