Interface
Sr Staff Software Engineer - Backend Core AI
Interface, San Jose, California, United States, 95199
Overview
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. About the Role
Were hiring a Staff Engineer AI Frameworks 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 modelsits 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. Youll 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 Youll Own
As a Staff Software Engineer specializing in Agentic AI Orchestration, you will be at the forefront of building the intelligent backbone of our platform. This pivotal role involves taking complete ownership of the architectural design and implementation that ensures our autonomous agents operate with unparalleled efficiency, security, and responsiveness. You will be instrumental in maintaining strict sub-second latency targets (under 1 second) across all critical operations, including sophisticated agent routing, the application of banking-grade security guardrails, and the secure, PII-safe execution and guardrails of tool calls. Beyond architecture, you will serve as the primary technical lead, guiding the strategic direction and hands-on development across several critical areas. This includes optimizing agent routing mechanisms, enhancing dynamic planning capabilities, evolving memory management systems for optimal token usage, establishing robust evaluation frameworks, and pioneering RL-based prompt tuning techniques. Your contributions will directly impact the reliability, safety, and performance of our next-generation AI agents. What Youll Do
This role demands a multifaceted technical leader capable of both high-level design and hands-on implementation. Your responsibilities will include: Lead Design and Implementation of Advanced Routing: Spearhead the architectural design and hands-on implementation of hierarchical and plan-based routing systems for our autonomous agents. Enforce tight latency budgets, specifically targeting performance within an 8001500 ms window to ensure seamless user interactions and agent responsiveness. Build Secure PII Pipelines: Develop and implement robust PII masking and transactional guardrails, ensuring secure data flows, idempotency, and transaction safety across all external tool calls made by our agents. Own Model Selection and Inference Strategy: Drive the strategic selection and optimization of inference models, including large language models, fine-tuned or custom small models, and leveraging high-performance inference engines to maximize throughput and minimize latency. Design Efficient Memory Layers: Architect memory layers for agents, including short-term rolling windows for immediate context, retrieval memory for efficient information access, and audited long-term state management to minimize token usage and optimize compute. Ship Comprehensive Observability: Implement observability solutions for understanding and debugging agent behavior, including per-turn token and latency budgeting, attribution, and alerting for anomalous behavior or performance degradation. Stand Up Evals & Reinforcement learning: Establish and maintain evaluation frameworks, regression suites to track performance over time, reward models for behavior optimization, and bandit algorithms for dynamic prompt/model/tool selection. Mentor and Elevate Standards: Act as a technical mentor for senior engineers, set high standards for code quality, incident response, and change management processes for reliable system evolution. What Were Looking For
Required Qualifications
To succeed in this role, you should possess a strong foundation in distributed systems and practical experience with AI agent technologies: Extensive Distributed Systems Experience: 8+ years of professional experience in designing, building, and maintaining high-throughput, low-latency distributed systems. Proficiency in at least one of the following programming languages is essential: Go, Rust, Java, C++, or Python. Proven LLM Agent Deployment: Demonstrated hands-on experience deploying, tuning and working with multi-agent frameworks and LLM agents, implementing function-calling mechanisms, or operating production-grade RAG systems at scale. Deep Streaming and Orchestration Knowledge: In-depth knowledge of streaming technologies (e.g., WebRTC/LiveKit, gRPC), asynchronous orchestration patterns, the use of idempotency keys, and ensuring exact-once semantics in distributed environments. Practical Security and Compliance Chops: Strong practical understanding and experience with security and compliance requirements, including secure PII handling, robust key management strategies, implementation of comprehensive audit trails, and policy enforcement within a highly regulated environment. Strong Optimization Instincts: Possess strong instincts and hands-on profiling experience in prompt engineering and token optimization for large language models, demonstrating an ability to maximize efficiency and minimize costs. Reinforcement Learning Expertise: Experience with RLHF (Reinforcement Learning from Human Feedback) / RLAIF (Reinforcement Learning from AI Feedback), reward modeling, online learning techniques (e.g., bandit algorithms), and building sophisticated evaluation harnesses for AI models Preferred Experience
Voice Systems Experience: Familiarity with voice systems, including managing STT and TTS latency, and practical experience with telephony or voice quality assurance. Banking/FinServ Background: Prior experience in the banking or financial services industry, including an understanding of relevant regulations and compliance standards. What Makes This Role Special
Youll define the core AI infrastructure powering autonomous financial workflows across millions of users Youll lead the engineering strategy behind multi-agent AI systemsdesigning how autonomous AI think Compensation
Compensation is expected to be between $210,000 - $240,000. Exact compensation may vary based on skills and location. What We Offer
Health: medical, dental, and vision insurance and wellbeing resources and programs Time away: Public holidays and discretionary PTO package for flexible days off with manager approval Financial: 401K, ESPP, Basic life and AD&D insurance, long-term and short-term disability Family: parental leave Development: Access to internal professional development resources. 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 do not discriminate and are committed to ensuring our hiring process is inclusive and accessible. #J-18808-Ljbffr
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. About the Role
Were hiring a Staff Engineer AI Frameworks 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 modelsits 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. Youll 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 Youll Own
As a Staff Software Engineer specializing in Agentic AI Orchestration, you will be at the forefront of building the intelligent backbone of our platform. This pivotal role involves taking complete ownership of the architectural design and implementation that ensures our autonomous agents operate with unparalleled efficiency, security, and responsiveness. You will be instrumental in maintaining strict sub-second latency targets (under 1 second) across all critical operations, including sophisticated agent routing, the application of banking-grade security guardrails, and the secure, PII-safe execution and guardrails of tool calls. Beyond architecture, you will serve as the primary technical lead, guiding the strategic direction and hands-on development across several critical areas. This includes optimizing agent routing mechanisms, enhancing dynamic planning capabilities, evolving memory management systems for optimal token usage, establishing robust evaluation frameworks, and pioneering RL-based prompt tuning techniques. Your contributions will directly impact the reliability, safety, and performance of our next-generation AI agents. What Youll Do
This role demands a multifaceted technical leader capable of both high-level design and hands-on implementation. Your responsibilities will include: Lead Design and Implementation of Advanced Routing: Spearhead the architectural design and hands-on implementation of hierarchical and plan-based routing systems for our autonomous agents. Enforce tight latency budgets, specifically targeting performance within an 8001500 ms window to ensure seamless user interactions and agent responsiveness. Build Secure PII Pipelines: Develop and implement robust PII masking and transactional guardrails, ensuring secure data flows, idempotency, and transaction safety across all external tool calls made by our agents. Own Model Selection and Inference Strategy: Drive the strategic selection and optimization of inference models, including large language models, fine-tuned or custom small models, and leveraging high-performance inference engines to maximize throughput and minimize latency. Design Efficient Memory Layers: Architect memory layers for agents, including short-term rolling windows for immediate context, retrieval memory for efficient information access, and audited long-term state management to minimize token usage and optimize compute. Ship Comprehensive Observability: Implement observability solutions for understanding and debugging agent behavior, including per-turn token and latency budgeting, attribution, and alerting for anomalous behavior or performance degradation. Stand Up Evals & Reinforcement learning: Establish and maintain evaluation frameworks, regression suites to track performance over time, reward models for behavior optimization, and bandit algorithms for dynamic prompt/model/tool selection. Mentor and Elevate Standards: Act as a technical mentor for senior engineers, set high standards for code quality, incident response, and change management processes for reliable system evolution. What Were Looking For
Required Qualifications
To succeed in this role, you should possess a strong foundation in distributed systems and practical experience with AI agent technologies: Extensive Distributed Systems Experience: 8+ years of professional experience in designing, building, and maintaining high-throughput, low-latency distributed systems. Proficiency in at least one of the following programming languages is essential: Go, Rust, Java, C++, or Python. Proven LLM Agent Deployment: Demonstrated hands-on experience deploying, tuning and working with multi-agent frameworks and LLM agents, implementing function-calling mechanisms, or operating production-grade RAG systems at scale. Deep Streaming and Orchestration Knowledge: In-depth knowledge of streaming technologies (e.g., WebRTC/LiveKit, gRPC), asynchronous orchestration patterns, the use of idempotency keys, and ensuring exact-once semantics in distributed environments. Practical Security and Compliance Chops: Strong practical understanding and experience with security and compliance requirements, including secure PII handling, robust key management strategies, implementation of comprehensive audit trails, and policy enforcement within a highly regulated environment. Strong Optimization Instincts: Possess strong instincts and hands-on profiling experience in prompt engineering and token optimization for large language models, demonstrating an ability to maximize efficiency and minimize costs. Reinforcement Learning Expertise: Experience with RLHF (Reinforcement Learning from Human Feedback) / RLAIF (Reinforcement Learning from AI Feedback), reward modeling, online learning techniques (e.g., bandit algorithms), and building sophisticated evaluation harnesses for AI models Preferred Experience
Voice Systems Experience: Familiarity with voice systems, including managing STT and TTS latency, and practical experience with telephony or voice quality assurance. Banking/FinServ Background: Prior experience in the banking or financial services industry, including an understanding of relevant regulations and compliance standards. What Makes This Role Special
Youll define the core AI infrastructure powering autonomous financial workflows across millions of users Youll lead the engineering strategy behind multi-agent AI systemsdesigning how autonomous AI think Compensation
Compensation is expected to be between $210,000 - $240,000. Exact compensation may vary based on skills and location. What We Offer
Health: medical, dental, and vision insurance and wellbeing resources and programs Time away: Public holidays and discretionary PTO package for flexible days off with manager approval Financial: 401K, ESPP, Basic life and AD&D insurance, long-term and short-term disability Family: parental leave Development: Access to internal professional development resources. 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 do not discriminate and are committed to ensuring our hiring process is inclusive and accessible. #J-18808-Ljbffr