Full Stack Engineer

Company Description

Elimai.ai specializes in creating AI-native and AI-enabled products to address the critical challenges faced by healthcare and manufacturing organizations. Our solutions enhance data analysis, uncover actionable insights, and optimize workflows to improve operational efficiency. By tailoring our services to meet unique business needs, we empower our partners to excel in their mission-critical objectives. We prioritize developing innovative, secure, and compliant technology solutions that are seamlessly aligned with real-world requirements.

Role Description

The Full Stack Engineer will design and build scalable software solutions by leveraging expertise in both front-end and back-end development. Day-to-day responsibilities include writing clean, efficient code, collaborating with cross-functional teams, debugging and optimizing applications, and contributing to the development of AI-powered platforms and tools. This full-time role requires the ability to operate effectively in a hybrid setting, based in Coimbatore, with flexibility for remote work.

Website: https://www.elimai.ai/

Compensation and Benefits:

Salary: 65,000-80,000 per month (based on experience).

Equity: Generous stock options

Flexible Work Environment: Remote/Hybrid

What Youll Bring:

0-2 years of experience in backend development, with a focus on building scalable, distributed systems.

Programming languages: MERN, Python, Java, or Go.

Designing RESTful APIs and exp. with frameworks like Spring Boot/FastAPI.

Advanced Database Expertise: PostgreSQL and MongoDB/ Firebase databases.

Key Responsibilities:

1. System Architecture & Design:

Design a distributed, highly available, scalable backend architecture.

Develop multi-threaded, high-concurrency systems optimized for real-time processing.

2. AI-Infused Workflows:

Work with AI engineers to embed intelligent agents, predictive models, and decision-making capabilities into backend workflows.

Design backend APIs to support AI-driven process optimization and NLP-powered automations.

3. Scaling & Performance Optimization

Implement horizontal scaling strategies to handle billions of API requests monthly without performance degradation.

Optimize database performance for terabyte-scale datasets, utilizing both SQL (PostgreSQL) and NoSQL (MongoDB, Firebase).

4. Cloud Infrastructure & Reliability:

Architect and manage a cloud-native infrastructure on AWS with advanced autoscaling, monitoring, and failover mechanisms.

Use container orchestration tools (Kubernetes/Docker) to deploy and manage scalable applications.

Set up CI/CD pipelines to ensure smooth, rapid deployments with zero downtime.

5.Cloud & DevOps Proficiency

Expertise in AWS services (EC2, S3, Lambda, RDS, DynamoDB) and cloud-native architectures

Strong experience with Docker and Kubernetes for containerization and orchestration.

Ability to design AI-first backend architectures with async processing, queues, and event-driven systems.

Experience working with embeddings, vector databases (Pinecone, Weaviate, FAISS, etc.).

Familiarity with prompt engineering, structured output parsing (JSON schemas), and evaluation frameworks.

Experience handling LLM reliability issues (hallucination control, guardrails, retries, validation layers).

Familiarity with model orchestration / multi-agent systems.