Job description
interface.ai is the industry’s-leading specialized AI provider for banks and credit unions, serving over 100 financial institutions. The company’s integrated AI platform offers a unified banking experience through voice, chat, and employee-assisting solutions, enhanced by cutting-edge proprietary Generative AI.
Our mission is clear: to transform the banking experience so every consumer enjoys hyper-personalized, secure, and seamless interactions, while improving operational efficiencies and driving revenue growth.
interface.ai offers pre-trained, domain-specific AI solutions that are easy to integrate, scale, and manage, both in-branch and online. Combining this with deep industry expertise, interface.ai is the AI solution for banks and credit unions that want to deliver exceptional experiences and stay at the forefront of AI innovation.
Location: India (Remote)
Function: Engineering – AI Platform
Level: Staff
Reports to: VP of Engineering / CTO
About the Role
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.
What You’ll Own
- 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
What We’re Looking For
Required Qualifications
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
Preferred Experience
- 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
What Makes This Role Special
- 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
At interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person’s unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.
