Solutions Architect

Solutions Architect Opportunity with Uplers for Qant

Location: Noida, India (Remote)

Opportunity Type: Full-Time Permanent (Managed by Qant)

Qant, a cutting-edge firm building the intelligence layer for investment funds, is seeking a talented Solutions Architect to design and implement AI infrastructure. This role involves creating RAG pipelines, agentic workflows, and LLM-powered research tools, all while adhering to strict enterprise security requirements.

Key Responsibilities:

• Architect end-to-end generative AI solutions, including RAG pipelines and agentic workflows.
• Define scalable and secure backend service architectures using Python and FastAPI.
• Design and optimize LLM deployment strategies, focusing on prompt engineering, retrieval grounding, and model evaluation.
• Establish patterns for agentic AI systems, including multi-step reasoning and memory management.
• Lead the technical evaluation and integration of vector databases and embedding models.
• Harden Linux environments and configure Nginx for API gateways with robust security controls.
• Mentor engineering teams on AI architecture best practices and security principles.
• Translate customer needs into technical architectures and drive incremental delivery.

Must-Have Skills:

• LangChain
• NoSQL Databases
• Terraform
• LLM (Large Language Models)
• MCP
• RAG (Retrieval-Augmented Generation)
• Solutions Architecture
• Python

Required Experience:

• 2+ years of production experience with LLMs and RAG systems.
• 2+ years designing or implementing agentic AI systems.
• Advanced Python expertise (typing, async, performance optimization).
• Proven solutions architecture experience with distributed systems and API strategies.
• Experience with production REST APIs using FastAPI.
• Strong hands-on experience with pandas, NumPy, SciPy.
• Linux (Debian) system administration and Nginx configuration.
• Demonstrated ability to lead technical strategy and mentor teams.

Preferred Experience:

• Enterprise AI deployments with strict data governance or on-prem constraints.
• Experience with agent frameworks like LangChain, LlamaIndex, AutoGPT, Crew AI.
• Fine-tuning, model evaluation, or working with local/open-source LLMs.
• Experience with high-speed NoSQL or vector databases.
• Familiarity with Containers/CI-CD (Docker, GitHub Actions) and infrastructure-as-code (Terraform).

Benefits:

• Competitive compensation package with potential equity.
• High ownership and direct impact on influential projects.
• Access to the latest tools and technologies in data science and finance.
• Opportunities for professional growth and learning.
• Flexible hours and remote work options.