Full Stack AI Engineer

Customerinsights.ai; Hyderabad, Gurugram District; Hybrid; INR 1,800,000 - 2,600,000; Full time

Job summary

Customerinsights.ai is hiring for a role focused on designing and building production-grade AI applications using modern frontend, backend, and GenAI technologies. You will craft UX for conversational AI and analytics, develop scalable APIs with Python, and integrate diverse LLMs into production systems.

You will work with RAG pipelines, vector search, and multi-agent workflows, ensuring secure access to enterprise data and APIs while aligning with architecture and CI/CD practices.

Qualifications

• 4–6 years of software engineering with strong full‑stack capability.
• 1–2 years hands‑on experience with LLMs or GenAI.
• Strong Python development skills and modern frontend experience.
• Experience building APIs, backend services and distributed apps.
• Experience integrating LLMs into production applications.

Responsibilities

• Design and build production-grade AI apps using modern frontend, backend, and GenAI tech.
• Develop UX for conversational AI, analytics, agent workflows, and decision-support apps.
• Build scalable backend APIs and services with Python frameworks (e.g., FastAPI).
• Integrate LLMs/models from providers and open-source ecosystems.
• Create RAG pipelines, semantic search, tool calling, and multi-agent workflows.
• Enable secure interaction with enterprise data, APIs, apps, and analytics workflows.
• Work with Snowflake, Databricks, relational DBs and vector stores.
• Implement authentication, authorization, SSO, RBAC, auditing, security controls.
• Contribute to architecture decisions, code reviews, CI/CD, and production support.
• Collaborate with Forward-Deployed AI Engineers to deploy customer use cases.

Skills

Full-stack development

LLMs / GenAI

Python

React / Next.js / TypeScript

APIs / backend services

LLM integration

RAG / vector search

Enterprise data platforms

Software engineering fundamentals

Authentication & authorization

Job description

Role & responsibilities

• Design and build production-grade AI applications using modern frontend, backend, and GenAI technologies.
• Develop intuitive user experiences for conversational AI, analytics, agent workflows, and decision-support applications.
• Build scalable backend APIs and services for AI-powered applications using Python-based frameworks such as FastAPI.
• Integrate LLMs and AI models from providers such as Anthropic, OpenAI, Azure OpenAI, and open-source models.
• Build and integrate RAG pipelines, knowledge retrieval, semantic search, tool calling, and multi-agent workflows.
• Develop capabilities that allow agents to interact securely with enterprise data, APIs, applications, and analytical workflows.
• Work with structured and unstructured data across Snowflake, Databricks, relational databases, object stores, and vector databases.
• Implement conversational and agentic workflows that can reason across data, documents, business rules, and domain-specific knowledge.
• Develop reusable UI components and product frameworks for multiple ciATHENA applications and use cases.
• Implement authentication, authorization, SSO, RBAC, audit logging, and enterprise security controls.
• Build AI observability, evaluation, tracing, monitoring, and feedback mechanisms.
• Optimize AI applications for performance, reliability, latency, and cost.
• Containerize and deploy services using Docker and cloud-native technologies.
• Participate in architecture decisions, code reviews, testing, CI/CD, and production support.
• Work closely with Forward-Deployed AI Engineers to rapidly configure and deploy customer-specific use cases.
• Translate product requirements and business workflows into working software with minimal handoffs.

Preferred candidate profile

• 4-6 years of software engineering experience with strong full-stack development capability.
• At least 1-2 years of hands-on experience building applications using LLMs or GenAI technologies.
• Strong Python development skills.
• Strong experience with React, Next.js, TypeScript, or equivalent modern frontend frameworks.
• Experience building APIs, backend services, and distributed applications.
• Hands-on experience integrating LLMs into production applications.
• Understanding of RAG, embeddings, vector search, prompt design, and agent architectures.
• Ability to work with enterprise data platforms and relational databases.
• Strong understanding of software engineering fundamentals, design patterns, testing, and maintainability.
• Experience building secure enterprise applications with authentication and authorization.