Applied AI Engineer

Applied AI Engineer – QuantaNova Technologies LLP

Role: Applied AI Engineer – Full Time, Onsite

Location: Gurugram, Haryana

QuantaNova Technologies is a new-age quantitative trading firm with a bold vision: to build a world-class, AI-first investment platform, democratizing institutional-grade quantitative investing across global markets—driven by scientific principles and academic rigor. Founded by graduates from the Massachusetts Institute of Technology (MIT), with experience managing multi-million-dollar portfolios at leading global hedge funds, we are building the next generation of systematic investment infrastructure.

We are seeking an Applied AI Engineer with strong software engineering fundamentals and proven experience building and deploying production-grade applications powered by large language models. The role requires end-to-end ownership of AI systems, from backend architecture and data infrastructure to retrieval, agentic workflows, and cloud deployment.

Key Responsibilities

• Design and deploy production-grade applications using LLMs, RAG, vector databases, and agentic workflows.
• Build AI systems for research, information retrieval, data search, code generation, and workflow automation.
• Develop backend services, APIs, data pipelines, retrieval systems, and orchestration layers supporting AI applications.
• Build agents that interact reliably with internal data, codebases, databases, APIs, and external tools.
• Own systems from architecture and implementation through deployment, monitoring, debugging, and iteration.
• Engineer for scalability, reliability, latency, observability, and cost efficiency.
• Continuously evaluate new models, frameworks, retrieval techniques, and AI tools for production use.

Requirements

• B.Tech/M.Tech in Computer Science or a related engineering discipline from a top institute.
• Minimum 2+ years of experience building and deploying LLM-based applications or AI workflows in production.
• Strong software engineering fundamentals, including system design, data structures, algorithms, APIs, databases, and testing.
• Strong proficiency in Python and experience building production backend systems.
• Hands-on experience with RAG, LLM agents, tool calling, embeddings, vector databases, and retrieval systems.
• Experience with data pipelines, backend services, databases, AWS, containers, and production deployment.
• Strong understanding of core machine learning concepts, including transformers, tokenization, embeddings, neural networks, and reinforcement learning, supported by mathematical maturity in probability, statistics, linear algebra, and optimization.
• Strong problem-solving and debugging ability across software, data, infrastructure, and AI systems.
• Ability to independently evaluate and adopt new AI tools, architectures, and engineering practices.

Bonus Skills

• Experience with PyTorch, NumPy, pandas, or the broader Python numerical ecosystem.
• Experience building code-generation agents, code-search systems, developer tools, or large-codebase retrieval systems.

What We Offer

• End-to-end ownership of production AI systems.
• Work at the intersection of software engineering, quantitative research, and modern AI.
• Direct collaboration with quantitative researchers and senior engineers in a high-performance environment.

Minimum base compensation for this role is 14LPA, with higher packages for strong candidates and possibility for performance linked incentives, tied directly to performance of the firm.