AI Engineer

Uplevyl

Dadri

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+

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Job summary

A technology firm is seeking an Artificial Intelligence Engineer to design and deploy cutting-edge AI solutions tailored for scalable community systems. The role requires strong expertise in LLM-based solutions and teamwork to understand real-world applications. Candidates should have a background in computer science and experience with ethical AI practices. This full-time position focuses on enhancing community engagement while navigating sensitive datasets, fundamentally supporting women-centric organizations.

Qualifications

4+ years of experience in LLM-based solutions, NLP, or AI system design.
Proven experience with RAG models, vector databases, and embedding pipelines.
Experience in handling domain-sensitive datasets and applying ethical AI practices.

Responsibilities

Design, develop, and deploy LLM-based AI solutions.
Implement advanced RAG models and embedding pipelines.
Work with multi-agent orchestration frameworks.

Skills

LLM-based solutions

NLP

Python

AWS

Ethical AI practices

RAG models

Vector databases

Education

Bachelor’s/Master’s in Computer Science, AI/ML, Data Science, or related field

Tools

PyTorch

TensorFlow

LangChain

LangGraph

Hugging Face Transformers

Job description

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At Uplevyl, we're redefining what intelligent communities look like. Through our AI-powered agents, we’re building scalable, agentic community systems that reduce manual work and increase member engagement—especially for women-centric organizations.

We’re looking for someone who gets community—because they’ve built one. Someone who understands the operational bottlenecks and the daily wins of growing a thriving space. Most importantly, someone who can now take that expertise and help us bring this new generation of agentic communities to life.

Key Responsibilities

Design, develop, and deploy LLM-based AI solutions tailored for scalable community systems.
Implement advanced RAG models, embedding pipelines, and vector databases (e.g., Pinecone, FAISS, Qdrant).
Work with multi-agent orchestration frameworks to build adaptive, intelligent workflows.
Fine-tune, pre-train, and evaluate LLMs for domain-specific applications.
Integrate AI/ML systems with AWS services such as SageMaker, Bedrock, ECS, and Cognito (or equivalent).
Collaborate with product and community teams to understand real-world use cases and translate them into robust AI solutions.
Ensure ethical AI practices when handling domain-sensitive datasets.
Stay updated on the latest AI research and apply innovative approaches to improve scalability and efficiency.

Performance Expectations

Deliver high-quality, production-ready AI models and pipelines within agreed timelines.
Demonstrate measurable improvements in community engagement and operational efficiency through AI-driven systems.
Maintain high standards of ethical AI practices and data governance.
Proactively identify challenges in scaling agentic communities and propose innovative solutions.
Communicate technical concepts clearly to both technical and non-technical stakeholders.
Work on cutting-edge AI systems at the intersection of community, engagement, and automation.
Contribute to building next-generation multi-agent and RAG-based solutions that will set industry benchmarks.
Be part of a mission-driven company focused on empowering women-centric organizations.
Balancing innovation with scalability in real-world deployments.
Navigating complexities of sensitive datasets while ensuring privacy and ethical AI usage.
Driving adoption of agentic community systems in diverse organizational settings.

Qualifications

Bachelor’s/Master’s in Computer Science, AI/ML, Data Science, or related field.
4+ years of experience in LLM-based solutions, NLP, or AI system design.
Proven experience with RAG models, vector databases (Pinecone, FAISS, Qdrant), and embedding pipelines.
Strong expertise in Python, PyTorch/TensorFlow, LangChain, LangGraph, Hugging Face Transformers.
Familiarity with AWS AI/ML stack (SageMaker, Bedrock, ECS, Cognito) or equivalent.
Experience in handling domain-sensitive datasets and applying ethical AI practices.
Hands-on experience with fine-tuning, pre-training, and evaluation of LLMs.

Seniority level