AI Engineer (LLM / GenAI)

Prescienceds; India; On-site; INR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary

Performance-based bonuses

Collaborative work environment

Job summary

Prescience Decision Solutions in Bengaluru, India, is seeking a highly skilled GenAI Engineer who will be responsible for designing, building, and deploying scalable AI solutions utilizing LLMs and agentic AI systems. The ideal candidate will have a strong background in GenAI frameworks and full-stack application development.

Responsibilities include developing secure architectures, optimizing LLMs, and working with multi-agent systems. Candidates should possess strong proficiency in Python, SQL, and various cloud platforms, alongside effective communication skills.

Qualifications

• Strong proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain).
• Hands-on experience with LLMs, RAG, embedding, and prompt tuning.
• Experience building AI agents and multi-agent systems.

Responsibilities

• Design and deploy secure, scalable GenAI architectures integrated into applications.
• Build and deploy REST APIs for AI/ML models.
• Fine-tune and optimize LLMs (GPT, VAEs, etc.).

Skills

Python

SQL

GenAI frameworks

LLMs

AWS

Azure

GCP

REST APIs

FastAPI

Node.js

React

TypeScript

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Prescience Decision Solutions | Full time

As an equal opportunity employer, we are dedicated to fostering a diverse and inclusive workplace, free from discrimination based on caste, religion, gender, sexual orientation, nationality, or other protected characteristics.

Role Overview

We are looking for a highly skilled GenAI Engineer to design, build, and deploy scalable AI solutions leveraging LLMs and agentic AI systems. This role requires strong expertise in GenAI frameworks, AI agent development, cloud platforms, and full-stack API-based application development.

Key Responsibilities

• Design and deploy secure, scalable GenAI architectures integrated into applications
• Build and deploy REST APIs for AI/ML models
• Work with Docker, Kubernetes in cloud environments (AWS/Azure/GCP)

GenAI & LLM Development

• Fine-tune and optimize LLMs (GPT, VAEs, GANs, transformer-based models)
• Implement RAG pipelines, embedding, and prompt engineering techniques
• Work with commercial and open-source LLMs (GPT, Claude, LLaMA, Phi)

Agentic AI Development

• Build and deploy AI agents using LangChain, LangGraph, CrewAI, Autogen, AgentFlow
• Implement multi-agent systems, orchestration, tool integration, and state management
• Develop autonomous or semi-autonomous workflows for business use cases

MLOps & Optimization

• Set up end-to-end MLOps pipelines (CI/CD, monitoring, retraining)
• Optimize performance, scalability, and infrastructure costs

Application Development & Data Integration

• Develop APIs using FastAPI / Node.js
• Work with React, TypeScript, async patterns, WebSockets/SSE
• Handle data integration using REST APIs, SQL, and external systems

Cross-Functional Collaboration

• Partner with Engineering, Product, and Data teams
• Communicate complex AI concepts clearly to technical and non-technical stakeholders
• Stay updated with the latest advancements in GenAI and AI agents

Required Skills

• Strong proficiency in Python, SQL, and GenAI frameworks (e.g., LangChain)
• Hands‑on experience with LLMs, RAG, embedding, and prompt tuning
• Experience building AI agents and multi‑agent systems
• Experience with cloud platforms (AWS/Azure/GCP) and containerization
• Strong knowledge of REST APIs and data integration
• Experience with FastAPI, Node.js, React, TypeScript
• Understanding of MLOps and deployment practices
• Strong analytical, problem‑solving, and communication skills

Preferred

• 4+ years of experience with GenAI/LLMs in production
• Experience with agent orchestration frameworks (CrewAI, LangGraph, Autogen)
• Exposure to client‑facing AI solutions or cross‑functional projects
• Open‑source contributions, research, or AI project portfolio

Requirements

• Competitive salary and performance‑based bonuses.
• Collaborative and supportive work environment.
• Chance to learn and grow with a talented team.