Banking is being reimagined—and customers expect every interaction to be
easy, personal, and instant
.
We are building a
universal banking assistant
that millions of U.S. consumers can use to transact across all financial institutions and, over time,
autonomously drive their financial goals
. Powered by our proprietary
BankGPT platform
, this assistant is positioned to
displace age-old legacy systems
within financial institutions and
own the end-to-end CX stack
,
unlocking a $200B opportunity
and potentially
replacing multiple publicly traded companies
.
Ultimately,
our mission is to drive financial well-being
for millions of consumers.
With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate,
we aim to
put financial well-being on autopilot
to help solve this problem.
About the Role
We're looking for a
Staff Engineer – Core Platform
to architect, scale, and evolve the distributed systems foundation that powers Interface.ai's next-generation AI experiences.
This is a
hands-on, high-impact engineering role
— you will design and build core platform components that enable
real-time AI interactions
,
secure orchestration
, and
low-latency execution
across millions of concurrent user sessions.
The ideal candidate is a
systems thinker
who thrives on solving large-scale engineering challenges in distributed, event-driven environments — someone who obsesses over
performance, reliability, and elegant architecture
, and who elevates the technical bar for the entire organization.
What You'll Own
As a Staff Engineer, you will be the
technical backbone
for the Core Platform team — defining architecture, mentoring teams, and ensuring engineering excellence across all systems.
You'll focus on:
Designing and scaling
low-latency, fault-tolerant distributed systems
serving real-time workloads.
Architecting
microservices and event-driven systems
that are secure, composable, and resilient under scale.
Integrating
Vector Databases and Embedding Stores
to support intelligent retrieval, RAG (Retrieval-Augmented Generation), and adaptive AI experiences.
Partnering with AI and Product teams to embed
LLMs and inference services
into the Core Platform, ensuring performance and observability.
Defining
technical standards
, best practices, and evolutionary architecture patterns across teams.
Driving continuous improvement in
code quality, observability, and deployment reliability
.
Acting as a
technical mentor




and multiplier — raising the bar for system design, code reviews, and debugging excellence.
What You'll Do
Architect and Build Distributed Systems:
Design microservice-based architectures that enable scalability, low latency, and fault isolation for AI-driven features.
Optimize System Performance:
Own performance at the platform level — from network I/O and API design to database indexing and caching strategies.
Enable AI Integrations:
Work closely with LLM engineers to design APIs and data pipelines supporting RAG, embeddings, and model-inference use cases.
Design Resilient Data Infrastructure:
Implement streaming and async systems (Kafka, Pulsar, or similar) to handle high-volume event traffic.
Drive Engineering Quality:
Establish patterns for clean code, contracts, testing, and documentation. Lead architecture and code reviews across pods.
Mentor and Coach:
Elevate senior engineers through structured mentorship, design walkthroughs, and technical guidance.
Champion Evolutionary Architecture:
Build for change — advocate for modular, observable, and testable systems that can evolve with business needs.
Improve Platform Resilience:
Implement retry, backoff, rate-limiting, and circuit-breaker patterns to ensure uptime and reliability at scale.
Collaborate Cross-Functionally:
Work with AI, data, DevOps, and product teams to define shared contracts, SLAs, and infrastructure standards.
What We're Looking For
Required Qualifications
Experience:
8+ years of experience in backend or platform engineering, including 2+ years in high-scale B2C or distributed systems environments.
Distributed Systems Mastery:
Deep understanding of
scalability, consistency, concurrency control, and fault tolerance
.
Low-Latency Systems Expertise:
Proven track record designing systems with strict SLA and sub-second response times.
Microservices Architecture:
Robust experience building, deploying, and maintaining service-oriented architectures with APIs, event streams, and async messaging.
Vector DBs & Embeddings:
Hands-on experience with
Weaviate, Pinecone, Qdrant, FAISS
, or similar; strong grasp of
RAG patterns
and
semantic retrieval
.
Programming Proficiency:




Expertise in
Go, Rust, Java, or Python
, and familiarity with modern frameworks (gRPC, GraphQL, REST).
Data Layer Knowledge:
Solid understanding of SQL/NoSQL databases (PostgreSQL, Cassandra, DynamoDB) and caching systems (Redis, Memcached).
Resilience & Observability:
Experience designing with telemetry, distributed tracing, chaos testing, and monitoring (Prometheus, OpenTelemetry).
Engineering Quality Mindset:
Passion for clean code, automated testing, CI/CD, and maintainability.
Bar-Raising Leadership:
Experience mentoring teams, enforcing code quality standards, and elevating design practices.
Preferred Qualifications
Experience building or scaling
real-time personalization or recommendation systems
.
Prior exposure to
LLM serving, RAG pipelines, and LLMOps frameworks
.
Familiarity with
Kafka
,
Flink
, or
Beam
for data streaming.
Contributions to open-source projects in distributed systems or AI tooling.
Deep understanding of
cloud-native architectures (Kubernetes, Istio, Terraform)
.
What Makes This Role Special
You'll define and scale the
core technical foundation
for AI systems serving millions of users.
You'll collaborate with world-class engineers across AI, platform, and product to deliver
real-time, intelligent experiences
.
You'll
raise the engineering bar
— shaping how code is written, reviewed, and deployed across teams.
You'll lead by example: mentoring senior engineers while remaining
hands-on
in architecture, design, and implementation.
You'll be part of an organization where
AI-first thinking
,
evolutionary architecture
, and
engineering craftsmanship
are core values.
#LI-Remote
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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.

📌 Staff Engineer Core Platform (Bengaluru)
🏢 interface.ai
📍 Bengaluru