Description :

Job Description Full Stack Engineer

Experience : 5 - 6 Years

Location : Bengaluru / Hyderabad / Mangalore

Employment Type : Full-time

About the Role :

We are hiring a talented and highly experienced Full Stack Engineer to join our fast-growing engineering team. In this role, you will design, develop, and deploy modern, scalable web applications using a combination of React, Node.js/Java/Python, microservices, and cloud-native technologies. The ideal candidate has hands-on coding expertise across the stack and practical experience integrating AI/LLM-based features into products.

You will collaborate closely with product managers, designers, AI/ML teams, and DevOps engineers to build reliable, performant, and innovative software systems that power mission-critical solutions.

This role requires end-to-end ownership, strong architectural thinking, and the ability to work with modern frontend, backend, cloud, and AI components.

Key Responsibilities :

1. Full Stack Development :

- Develop responsive, high-performance UI components using React, TypeScript, Redux/Zustand, and modern UI patterns.

- Build backend applications using Node.js (Express/Nest.js) or Python (FastAPI/Django) or Java-based frameworks.

- Implement and maintain RESTful APIs and GraphQL endpoints.

- Write clean, modular, testable, and maintainable code following engineering best practices.

- Convert product requirements into scalable technical solutions with minimal supervision.

- Ensure cross-browser compatibility and optimal performance across devices.

2. AI / LLM Integration :

- Integrate LLM APIs (OpenAI, Anthropic, Azure OpenAI, Vertex AI, etc.) into front-end and back-end systems.

- Work closely with AI/ML teams to consume internal inference APIs, vector search pipelines, and ML workflows.

- Build AI-driven features such as :

Chat-based AI assistants

RAG/Hybrid search pipelines

Document processing, embeddings & retrieval systems

Automated workflows powered by AI

- Implement safe, efficient prompt engineering and LLM invocation strategies.

- Optimize LLM workflows for latency, cost, throughput, and reliability.

3. Architecture & System Design :

- Design and develop scalable microservices and distributed systems.

- Create architecture diagrams, API contracts, data flow models, and integration blueprints.

- Apply distributed system principles including caching, asynchronous messaging, load balancing, and resiliency patterns.

- Collaborate with senior engineers on technical design and system modernization efforts.

4. Cloud & DevOps :

- Deploy and manage applications on AWS, GCP, or Azure.

- Work with containerization and orchestration tools : Docker, Kubernetes.

- Contribute to CI/CD pipelines using tools like GitHub Actions, Jenkins, or GitLab CI.

- Monitor system performance using tools like Prometheus, Grafana, CloudWatch, Stackdriver.

- Support DevOps practices and troubleshoot cloud deployment issues.

5. Database & Storage :

- Work with relational databases : PostgreSQL, MySQL.

- Work with NoSQL systems such as MongoDB, DynamoDB, Redis.

- Design efficient database schemas, indexes, caching strategies, and optimize query performance.

6. Collaboration, Leadership & Delivery :

- Work cross-functionally with designers, PMs, AI engineers, DevOps, and QA teams.

- Review code, mentor junior engineers, and enforce engineering best practices.

- Participate in sprint planning, grooming, architectural reviews, and technical roadmap discussions.

- Take end-to-end ownership of feature deliveryfrom design to deployment.

Required Skills & Experience :

Frontend Skills :

- 3 - 4+ years of strong hands-on experience with React.

- Strong knowledge of JavaScript/TypeScript, hooks, component architecture, and state management (Redux/Zustand).

- Familiarity with Next.js, Vite, Webpack, or similar tooling.

Backend Skills :

- Expertise in at least one :

Node.js (Express/Nest.js)

Python (FastAPI/Django)

Java (Spring Boot)

- Experience designing REST APIs, GraphQL schemas, and structured backend logic.

- Strong understanding of authentication/authorization (JWT, OAuth2).

- Good knowledge of design patterns and service-oriented architecture (SOA).

AI Integration :

- Experience integrating LLM APIs or other ML inference endpoints.

- Understanding of embeddings, vector databases (Pinecone, FAISS, Weaviate).

- Familiarity with RAG pipeline concepts and prompt engineering.

- Ability to implement AI features securely and efficiently.

Microservices & Cloud :

- Strong experience with microservices, event-driven architecture, and messaging systems :

Kafka, SQS, RabbitMQ, Pub/Sub

- Hands-on cloud deployment experience using AWS, GCP, or Azure.

- Docker/Kubernetes experience in production environments.

Testing & Quality :

- Hands-on experience with testing frameworks :

Jest, React Testing Library

Mocha/Chai, PyTest, JUnit

- Strong debugging, profiling, and performance optimization skills.

Nice-to-Have :

- Experience with serverless technologies (AWS Lambda, Cloud Functions).

- Knowledge of CI/CD and Infrastructure-as-Code (Terraform, CloudFormation).

- Exposure to MLOps tools and ML pipelines.

- Understanding of security best practices (OWASP, IAM, API security).

- Experience working in Agile/Scrum environments.