Technical Project Manager & Scrum Master

Job Title: AI Engineer

Location:

Type:

About Us

Uplevyl

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. 

Opportunities & Challenges

• Opportunities:

   
• 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. 

• Challenges:

   
• 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. 
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