About the Role

We are looking for a hands-on Engineering Manager to lead a Bengaluru-based product engineering team responsible for delivering AI-powered banking products across voice, chat, and digital channels.

This role is part of our India offshore development team and requires close partnership with US-based product, engineering, AI, customer, and leadership teams. You will be responsible for driving execution, technical quality, delivery predictability, and engineering ownership from the Bengaluru team.

This is not a pure people-management role. We need an engineering leader who can stay close to architecture, code quality, debugging, production reliability, and team execution.

What You’ll Own

• Lead and grow a high-performing Bengaluru engineering team.
• Drive execution across product features, backend services, integrations, platform improvements, and reliability initiatives.
• Partner with US stakeholders to clarify priorities, manage dependencies, and deliver with predictability.
• Stay involved in architecture reviews, code reviews, technical tradeoffs, debugging, and production issue resolution.
• Ensure systems are scalable, secure, observable, maintainable, and production-ready.
• Build a culture of ownership, engineering discipline, accountability, and continuous improvement.
• Mentor engineers, senior engineers, and tech leads to improve technical depth and execution maturity.

What You’ll Do

Lead Product Engineering Execution

• Convert product and customer priorities into clear engineering plans.
• Manage sprint execution, estimation, release readiness, risk tracking, and delivery communication.
• Ensure the offshore team operates with clarity, urgency, and accountability.
• Identify blockers early and drive resolution across teams.

Stay Hands-On Technically

• Review architecture, APIs, service design, data flows, and integration patterns.
• Guide engineers on scalable design, clean implementation, testing, and maintainability.
• Help debug complex backend, performance, reliability, and production issues.
• Raise the quality bar through strong technical judgment and practical engineering standards.

Drive AI-First Engineering

• Support development of AI-powered capabilities across voice, chat, automation, and employee-assist workflows.
• Work with AI, data, product, and platform teams to integrate AI capabilities into production systems.
• Encourage responsible use of LLM tools, automation, and AI-assisted development.
• Help ensure AI-driven product experiences are reliable, testable, secure, and customer-ready.

Improve Quality and Reliability

• Strengthen practices across code reviews, testing, CI/CD, observability, monitoring, and incident learning.
• Track quality metrics such as latency, reliability, defects, user impact, and operational stability.
• Balance fast delivery with long-term maintainability, reliability, and security.

What We’re Looking For

Required Qualifications

• 8+ years of software engineering experience, with strong backend, platform, or product engineering depth.
• 2+ years of engineering management, team leadership, or technical leadership experience.
• Strong hands-on background in backend systems, APIs, distributed systems, scalable architectures, and production-grade software.
• Ability to deep-dive into architecture, code, data flows, integrations, debugging, and production issues.
• Experience leading engineers while remaining technically involved.
• Strong understanding of system design, microservices, cloud systems, CI/CD, testing, observability, and reliability.
• Experience delivering customer-facing or business-critical product systems in production.
• Strong execution discipline across planning, estimation, release management, quality, and risk tracking.
• Ability to work effectively with US-based product, engineering, and leadership teams in a distributed/offshore model.
• Strong written and verbal communication skills.
• High ownership mindset with the ability to operate in ambiguity.
• Willingness to work from the Bengaluru office 5 days a week.

Strongly Preferred Qualifications

• Experience building or managing teams working on AI-powered, ML-powered, LLM-powered, conversational AI, or automation products.
• Experience with voice, telephony, real-time chat, messaging, streaming, or low-latency systems.
• Experience in fintech, banking, payments, enterprise SaaS, customer experience platforms, or regulated environments.
• Exposure to agentic AI systems, LLM workflows, RAG, embeddings, evaluation pipelines, or AI-assisted engineering tools.
• Experience with cloud-native systems using AWS, GCP, or Azure.
• Experience with observability, monitoring, incident response, performance tuning, and reliability engineering.
• Experience working with globally distributed teams across India and US time zones.
• Prior experience in a high-growth startup or high-accountability product engineering environment.

Why Join Interface.ai

• Work on AI-native products transforming banking experiences.
• Build systems across voice, chat, automation, personalization, and financial workflows.
• Join a high-growth company with strong product-market fit.
• Work closely with global product, engineering, AI, and customer teams.
• Lead a Bengaluru engineering team where strong ownership, quality, and execution have visible impact.

About the Role

We are building an AI-native platform where agentic systems, real-time services, and distributed infrastructure converge to power intelligent financial products. We are looking for a Senior Platform Engineer who is deeply technical, AI-first by mindset, and excited to build foundational systems through code.

This is a senior individual contributor role for someone who:

• Thinks in distributed systems
• Codes extensively and confidently
• Understands AI-native architectures
• Builds durable, scalable platforms
• Use AI tools (Cursor, MCP, Claude, etc.) to write, review and ship code- not as an experiment, but as default practice
• Raises the engineering bar for everyone around them

You will write production-grade code daily and own critical components of our core platform

What You’ll Do

Build AI-First Platform Systems

• Design and implement core platforms that power multi-agent orchestration, real-time decisioning, and AI workflows.
• Build structured control layers around LLM integrations to ensure reliability and low latency.
• Develop abstractions that allow AI systems to operate safely and predictably at scale.
• Contribute to evaluation, monitoring, and guardrail systems for AI development lifecycle and agentic architectures.

Engineer High-Performance Distributed Systems

• Design and build low-latency infrastructure platforms
• Optimize resource utilization and costs
• Enable streaming and event-driven platforms to be hosted
• Build fault tolerance, resiliency, and failovers.
• Enable reducing tail latency and eliminate performance bottlenecks.

Code with Ownership

• Write production-quality code in Python and at least one systems/backend language (Node.js or Go preferred).
• Use AI as an active part of how you write, review, refactor, and debug — not a shortcut, but a force multiplier on your engineering judgment.
• Review code with rigor and raise engineering standards.
• Refactor and simplify, and build abstractions over complex infrastructure systems for maintainability.

Strengthen Platform Foundations

• Build reusable service frameworks and platform abstractions.
• Improve observability, logging, metrics, and tracing.
• Harden authentication, authorization, and secure service-to-service communication.
• Drive architectural improvements through RFCs and technical proposals.

Collaborate Across AI & Product Teams

• Work closely with engineers and product teams.
• Translate product needs into scalable platform capabilities.
• Build a security first mindset and frameworks to enable secure SDLC
• Support compliance, security, and governance requirements.

What You’ll Bring

Required

• 7+ years of backend or distributed systems engineering experience.
• Strong proficiency in Python and at least one backend language (Node.js or Go).
• Proven experience with observability and tracing systems (OpenTelemetry, Prometheus, Grafana). 
• Hands-on experience with IaC tools — Terraform, Pulumi, or AWS CDK — architecting infrastructure that is scalable, repeatable, and version-controlled. 
• Experience with CI/CD pipeline design (Jenkins, GitHub Actions, ArgoCD, GitOps workflows).
• Hands-on experience with Kubernetes, Helm, Terraform, and declarative infrastructure management.
• Deep understanding of distributed systems, concurrency, and performance optimization.
• Experience building high-availability, production-scale systems.
• Hands-on experience designing APIs and microservices.
• Strong debugging skills across complex distributed environments.
• Experience deploying systems in cloud-native environments. 
• AI- native workflow: Build with AI daily: creating agents, automating analyses, prototyping with code, building custom workflows. The specific tools don't matter (Cursor, Copilot, Claude, Replit, custom scripts — all count); what matters is that you've moved beyond prompting into building.

Strongly Preferred

• Experience working with LLMs or AI-driven systems in production.
• Familiarity with agentic architectures or multi-agent orchestration.
• Experience with streaming systems and event-driven architectures.
• Experience building systems under strict latency constraints.
• Experience in fintech or regulated environments

Bonus Points

• Experience with platform product thinking—prioritizing developer empathy and user feedback.
• Previous work in platform engineering or internal developer portals.

Why Join Us

• Build core platform systems that power one of the fastest-growing AI companies in fintech.
• Shape developer experience, infrastructure standards, and reliability practices for an AI-first ecosystem.
• Work in a high-trust, fast-growth environment where innovation meets real-world impact.
• This role directly impacts:
  • Multi-agent orchestration
  • Low-latency real-time systems
  • Reliability of customer-facing AI
  • System scalability under growth
  • Compliance and security guarantee

Compensation

•  Base Salary Range is expected to be between $170,000 - $210,000, plus performance bonus and equity options. Exact compensation may vary based on skills and location.

We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role.

How We Work

Every Engineer builds with AI daily. Our standard toolkit is Cursor, MCP integrations,  Claude, and custom AI agents — and we onboard every new hire on these tools in their first week. We hold a high quality bar and move at startup speed. Flat organization. No empire-building.

Our Values

• Act Like You're the Founder: Own the outcome from start to finish
• No Fear. Speak Your Mind: Candor moves us forward
• Pursuit of Excellence: Raise the bar, every time
• AI-First Mindset: Think automation, intelligence, and scale-first in every solution
• Don't Assume. Seek to Understand: Start with questions, not conclusions

What We Offer

• 💡 100% paid health, dental & vision care
• 💰 401(k) match & financial wellness perks
• 🌴 Discretionary PTO + paid parental leave
• 🧠 Mental health, wellness & family benefits
• 🚀 A mission-driven team shaping the future of banking

About the Role

We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems.

This role requires someone who:

• Has built complex distributed backend systems
• Understands low-latency architectures (voice, telephony, streaming, chat)
• Is fluent in modern agentic AI engineering
• Thinks like a founder
• Leads by building
• Raises the engineering bar

You will architect, review, code, debug, and ship along with building your high performance engineering team.

What You’ll Do

1. Lead with an AI-First Engineering Mindset

• Drive AI-first thinking across product architecture and execution.
• Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows.
• Champion agentic engineering principles across your team.
• Evaluate and adopt emerging AI capabilities pragmatically and responsibly.
• Raise the quality bar for AI-generated and human-written code alike.

2. Build and Orchestrate Agentic Systems

• Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use.
• Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies.
• Actively participate in the code base
• Design orchestration layers that convert AI reasoning into reliable execution.
• Build control frameworks around LLMs for grounding, safety, and deterministic behavior.
• Develop evaluation pipelines to ensure agents meet production standards.

3. Own Low-Latency, High-Concurrency Backend Systems

• Design distributed backend systems serving real-time voice and chat interactions.
• Optimize latency-sensitive systems across telephony, streaming, and API layers.
• Build event-driven architectures that handle high concurrency and fault tolerance.
• Implement state management and memory layers for conversational agents.
• Drive reliability, failover, and graceful degradation strategies.

4. Ship Production-Ready AI Products

• Ensure AI-generated outputs translate into robust, testable, production-quality code.
• Maintain high standards for observability, monitoring, and debugging.
• Build automation and testing strategies for agent-based systems.
• Ensure security, compliance, and safe handling of financial data.
• Create durable systems that scale with increasing AI complexity.
• Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality

5. Operate Like a Founder

• Demonstrate extreme ownership across product, architecture, and delivery.
• Drive clarity in ambiguous problem spaces.
• Move quickly without compromising engineering rigor.
• Build and grow a high-performance team with bias to action.
• Set culture around accountability, urgency, and craftsmanship.

Required Qualifications

• 8+ years of backend engineering experience building distributed systems.
• Strong experience with low-latency systems such as:
• Voice / telephony platforms
• Real-time streaming systems
• Chat or messaging architectures
• 3+ years working with LLM-powered or AI-driven systems in production
• Hands on experience building systems that interface with LLMs.
• 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers
• Hands-on experience designing and orchestrating agentic workflows.
• Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc)
• Deep understanding of distributed systems, concurrency, and reliability.
• Experience managing engineers while remaining deeply hands-on.
• Experience deploying AI systems in cloud environments.
• Product Mindset: You care deeply about the product experience

Strongly Preferred

• Experience building AI-native customer-facing products.
• Experience in Fintech or regulated environments.
• Familiarity with multi-agent architectures and reasoning frameworks.
• Experience with reinforcement learning or adaptive optimization loops.
• Experience building structured evaluation and monitoring for AI agents.

Who You Are

• You care deeply about engineering quality and raise the bar for everyone around you.
• You demonstrate AI-first approaches when solving problems.
• You move fast and take ownership beyond your scope.
• You operate with founder-level urgency and accountability.
• You build teams that execute with discipline and craftsmanship.
• You are comfortable orchestrating multiple AI agents to produce production-ready outcomes.

What Makes This Role Matters?

Agentic engineering is changing how products are built.

This role defines how:

• AI systems reason in real time
• Voice and chat agents operate under latency constraints
• Financial workflows become autonomous yet safe
• Multiple AI agents collaborate to produce deterministic, high-quality outcomes

You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences.

We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role.

Compensation: 

•  Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options  Exact compensation may vary based on skills and location.

The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits.

What We Offer

• 💡 100% paid health, dental & vision care
• 💰 401(k) match & financial wellness perks
• 🌴 Discretionary PTO + paid parental leave
• 🧠 Mental health, wellness & family benefits
• 🚀 A mission-driven team shaping the future of banking

About the Role

As the Director of Security & Privacy Engineering, you will report to the VP of Engineering and play a pivotal role in defining and executing interface.ai’s enterprise-wide security and privacy strategy.You will build and lead a program that ensures our AI products and cloud infrastructure are secure, compliant, and resilient, fostering customer trust and meeting regulatory requirements. This is a strategic and hands-on leadership role influencing technology, governance, and culture across the organization. You will lead the development of a secure, compliant, and resilient environment for our AI products and cloud infrastructure — ensuring customer trust and adherence to industry regulations. This is both a strategic and hands-on leadership role that will influence technology, governance, and culture across the organization.

You will be responsible for leading the company’s cybersecurity, privacy, and compliance programs; establishing strong internal controls; managing security risk; and driving security-by-design practices across all engineering and AI initiatives.

What you will do:

As a Director of Security & Privacy Engineering you will be reporting to the  VP of Engineering and will be responsible for:

• Own all aspects of Security (excluding physical security), Privacy, and Compliance across the company.
• Develop and enforce security and privacy policies, procedures, and standards, ensuring organization-wide compliance.
• Lead cybersecurity incident response and continuous risk assessment programs.
• Partner with the executive team to align security strategy with business goals and risk tolerance.
• Oversee compliance with GLBA, FFIEC, SOC 2, and other applicable frameworks.
• Champion privacy-by-design principles across product and AI initiatives.
• Lead security and privacy initiatives for AI-powered products, ensuring safe deployment of generative AI, LLM-driven systems, and AI workflows through secure architecture, risk mitigation, and responsible AI governance.
• Partner with Sales, Legal, Compliance, and Product teams to address security inquiries and due diligence requests.
• Deliver executive-level security and risk reports to leadership and the board.
• Collaborate with Engineering and Cloud Infrastructure teams to embed Dev SecOps and secure architecture practices.
• Build, mentor, and grow a high-performing team of security and privacy engineers.
• Foster a culture of proactive risk management, innovation, and continuous improvement.

Requirements

• 12+ years of cybersecurity leadership experience, ideally within financial services, banking, fintech, or regulated environments.
• AI & Generative AI Security Mindset: Experience securing AI-driven platforms, LLM workflows, or AI-powered products, including awareness of emerging AI risks such as prompt injection, data leakage, and model misuse
• Cloud Security Expertise: Strong experience securing cloud-native infrastructure, particularly AWS, including identity management, network security, container security, and infrastructure protection
• Security Architecture & DevSecOps: Ability to embed security-by-design practices across distributed systems, APIs, microservices, and CI/CD pipelines
• Data Security & Privacy Engineering: Deep knowledge of data protection, encryption, identity and access management (IAM), and threat modeling, especially for sensitive financial data
• Regulatory & Compliance Leadership: Strong understanding of GLBA, FFIEC, SOC 2, and enterprise security frameworks, with experience building compliant security programs
• Executive Leadership & Communication: Proven ability to lead security programs, communicate risk to executive stakeholders, and build high-performing security and privacy engineering teams
• Bachelor's degree in Information Security, Computer Science or related field.

Preferred:

• Master’s degree in Information Security, Computer Science, or related field.
• Experience in a startup or high-growth SaaS/AI company.
• Certifications such as CISSP, CISM, CCSP, or ISO 27001 Lead Implementer.

Why Join Us

• Shape the security, privacy, and trust strategy for an industry-defining platform.
• Drive innovation in cloud, AI, and data privacy while ensuring compliance and trust at scale.
• Work in a high-impact, mission-driven environment where your leadership directly influences millions of banking customers. 

What We Offer

• 💡 100% paid health, dental & vision care
• 💰 401(k) match & financial wellness perks
• 🌴 Discretionary PTO + paid parental leave
• 🧠 Mental health, wellness & family benefits
• 🚀 A mission-driven team shaping the future of banking

About the Role

We are seeking a highly skilled and passionate Platform Engineer to help redefine how infrastructure and operations are delivered to development teams. This is a role for someone moving beyond traditional DevOps into a space focused on developer enablement, tooling, and abstractions that make engineering teams more productive and self-sufficient.

As a Platform Engineer, you’ll be instrumental in designing and building internal platforms, frameworks, and interfaces (e.g., Web UIs, CLI tools, ChatOps interfaces) that abstract the complexity of infrastructure, enabling developers to focus on building features and shipping code confidently.

Key Responsibilities

• Tooling & Automation: Design, build, and maintain self-service tooling for developers—enabling them to provision infrastructure, deploy applications, and monitor systems with minimal friction.
• Abstraction & Interface Building: Create easy-to-use abstractions and interfaces (like Web UIs, chatbots, and CLIs) that simplify operational tasks and workflows.
• Infrastructure as Code (IaC): Architect and maintain scalable, repeatable infrastructure using Terraform, Pulumi, or similar tools.
• Cloud Engineering: Work deeply within cloud platforms (AWS/GCP/Azure), leveraging native services to optimize performance, cost, and scalability.
• CI/CD Systems: Build and optimize robust continuous integration and deployment pipelines that reduce lead time and improve reliability.
• API Gateways & Service Meshes: Manage API gateways, ingress controllers, and service mesh implementations for resilient, observable services.
• Observability: Establish centralized monitoring, alerting, metrics, APM, and logging solutions to ensure system reliability and developer insight.
• Cost Optimization: Implement cost management tooling and visibility features to ensure sustainable platform usage.
• Environment Management: Develop systems for ephemeral and on-demand environments to support testing, experimentation, and feature validation.
• Experimentation Frameworks: Support teams with infrastructure and tooling for A/B testing and canary deployments.
• Security & Governance: Ensure platform tools comply with organizational security policies and audit requirements.
• Developer Collaboration: Serve as a partner to engineering teams, gathering feedback, running internal demos, and iterating quickly to improve the developer experience.
  
  

What We’re Looking For

• Strong coding background in languages such as Go, Python, TypeScript, or similar.
• Hands-on experience with IaC tools (Terraform, Pulumi, AWS CDK, etc.).
• Deep knowledge of cloud environments (AWS, GCP, or Azure).
• Experience with container orchestration platforms (Kubernetes, ECS, Nomad).
• Proficient in CI/CD pipelines (Jenkins, ArgoCD, GitHub Actions, etc.).
• Familiarity with API gateways, service mesh, and rate limiting
• Solid understanding of monitoring/alerting (Prometheus, Grafana), APM tools (Datadog, New Relic), and centralized logging (ELK, Loki, or similar).
• Experience managing costs in cloud environments.
• Proven ability to build interfaces and platforms (dashboards, chatbots, CLI tools).
• Strong communication skills and ability to collaborate cross-functionally.

Bonus Points

• Experience with platform product thinking—prioritizing developer empathy and user feedback.
• Previous work in platform engineering or internal developer portals.

Exposure to feature flag frameworks and progressive delivery tools.

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: Strong 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.
  
  
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