PRESCIENCE - AI Engineer

Prescience Decision Solutions (A Movate Company); Karnataka; On-site; INR 4,000,000 - 7,500,000; Full time

Benefits offered by this job

Competitive salary

Performance-based bonuses

Insurance plans

Collaborative environment

Learning opportunities

Job summary

Prescience Decision Solutions (A Movate Company) is seeking a senior GenAI architect to design secure GenAI architectures and deploy AI/ML services at scale. You will build REST APIs, containerize using Docker/Kubernetes, and collaborate across engineering, product, and data teams.

The role emphasizes hands-on development with LangChain, LLMs, RAG, and multi-agent systems, along with end-to-end MLOps practices and cloud deployments on AWS/Azure/GCP.

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.
• 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.
• Excellent communication and problem-solving skills.

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).
• Fine-tune and optimize LLMs and implement RAG pipelines.
• Develop AI agents using LangChain, LangGraph, CrewAI, Autogen, AgentFlow.
• Set up end-to-end MLOps pipelines (CI/CD, monitoring, retraining).
• Develop APIs with FastAPI / Node.js and front-end with React/TypeScript.
• Collaborate with Engineering, Product, and Data teams; communicate complex AI concepts.

Skills

Python

SQL

GenAI frameworks

LLMs

Prompt tuning

Agent development

Multi-agent systems

Cloud platforms

REST APIs

Docker

Kubernetes

LangChain

Communication

Tools

LangChain

Docker

Kubernetes

FastAPI

Node.js

React

TypeScript

Job description

• 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).

Job Description

Key Responsibilities :

Solution Architecture & Deployment

• 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.
• Use tools like Git, Docker, Kubernetes, vector databases.

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

• 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.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive insurance plans.
• Collaborative and supportive work environment.
• Chance to learn and grow with a talented team.
• A positive and fun work environment.