Staff Backend Engineer – Core AI Platform

Location: India (Remote)
Function: Engineering – AI Platform
Level: Staff
Reports to: VP of Engineering / CTO

We’re hiring a Staff Backend Engineer – Core AI Platform to architect and lead the development of the foundational multi-agent infrastructure powering the next generation of intelligent systems for financial institutions.

This role is not about plugging in pre-built models—it’s about designing and scaling custom AI orchestration frameworks that bind language models, memory, judgment modules, and tool use into autonomous systems that are trustworthy, composable, and policy-aligned.

You’ll work at the intersection of machine learning, distributed systems, and agentic reasoning, partnering with researchers, backend engineers, and product leaders to bring real-time, LLM-driven intelligence into production at scale.

This is a rare opportunity to define and build the AI runtime and execution architecture for mission-critical agents in a high-regulation, high-trust industry.

• Architect a multi-agent AI framework for orchestrating LLMs, tools, memory, and decision modules in live user-facing systems
• Build and optimize low-latency, distributed inference systems that meet real-time SLAs for transactional environments
• Develop modular components for task planning, reward routing, fallback handling, and multi-turn reasoning
• Design developer-facing APIs and tooling to allow AI product teams to safely extend and compose agentic functionality
• Integrate vector stores, custom retrieval pipelines, model evaluators, judgment layers, and auto-tuning workflows
• Drive the implementation of prompt tuning, reward modeling, and LLM-as-a-Judge techniques in production loops
• Collaborate with research to productionize new RL, planning, or alignment strategies
• Establish architectural best practices for extensibility, observability, and trust in AI-enabled systems

• 8+ years of backend or platform engineering experience, with at least 2 years building or deploying AI/ML systems
  
• Prior hands-on experience building ML models or training pipelines—you know how models learn, behave, and break
• Expert knowledge of LLM system design, agent architectures, and Reinforcement Learning techniques
• Deep experience with Node.js, asynchronous architecture, and performance-critical backend systems
• Proven track record building distributed, event-driven systems in high-throughput environments
• Experience building real-time inference systems that integrate LLMs with retrieval, memory, or tool use
• Strong systems design skills: designing modular, fault-tolerant, observable software at scale
• Demonstrated ability to lead architectural design and cross-functional engineering initiatives

• Experience building multi-agent systems or intelligent orchestration engines
• Familiarity with vector databases, semantic search, and prompt engineering techniques
• Comfort integrating ML eval frameworks and offline/online experimentation pipelines
• Open-source contributions to LLM tooling or infrastructure a plus

• You’ll define the core AI infrastructure powering autonomous financial workflows across millions of users
• You’ll lead the engineering strategy behind multi-agent AI systems—designing how autonomous AI thinks, adapts, and acts
• You’ll build for speed, scale, and compliance, solving real-world challenges in applied alignment, observability, and modularity
• You’ll work with a team that combines world-class AI research, backend engineering, and product-first thinking to move fast with purpose