Senior Backend Engineer

FlexAI

  • San Jose, California
  • 30+ days ago

    Highlights

    As a Senior Backend Engineer , you'll drive backend architecture, scale platform services, and build high-performance infrastructure components that power AI workloads in production environments — influencing how the platform evolves from Beta to enterprise-grade deployment. FlexAI is looking for a Senior Backend Engineer (Infrastructure & AI Platform) with deep Golang expertise to architect and build the core backend systems powering our next-generation AI compute and PaaS platform.

    Numbers & Facts

    LocationSan Jose, California

    Description

    Role Overview

    FlexAI is looking for a Senior Backend Engineer (Infrastructure & AI Platform) with deep Golang expertise to architect and build the core backend systems powering our next-generation AI compute and PaaS platform. This role sits at the intersection of distributed systems, cloud infrastructure, and AI platform engineering — enabling large-scale model training, inference, and orchestration across heterogeneous compute. This is not a traditional backend role; you will be building platform-grade systems that support AI runtimes, scheduling, resource orchestration, and multi-tenant cloud infrastructure.


    As a Senior Backend Engineer, you'll drive backend architecture, scale platform services, and build high-performance infrastructure components that power AI workloads in production environments — influencing how the platform evolves from Beta to enterprise-grade deployment. Expect high ownership and technical autonomy in a research-driven, deep-tech environment — not SaaS CRUD apps.


    This position is In-Person and located at our San Jose, CA Office.

    What You'll Do

    Core Platform & Infrastructure Backend:

    • Architect and develop high-performance Golang services for FlexAI's AI PaaS and infrastructure platform
    • Build internal APIs powering model deployment, job scheduling, and compute lifecycle management
    • Develop components interfacing with GPU/compute infrastructure and AI runtimes

    Distributed Systems & Scalability:

    • Design and scale microservices and event-driven systems for high-throughput AI workloads
    • Optimize for low latency, high concurrency, and fault tolerance
    • Implement service-to-service communication (gRPC/REST, message queues, async pipelines)
    • Drive reliability, observability, and resilience across services

    AI Platform Integration:

    • Collaborate with AI/ML and Runtime teams to integrate systems with training pipelines, inference infrastructure, experimentation workflows, and dataset/artifact management
    • Enable orchestration across cloud and on-prem environments
    • Build abstractions that simplify AI infrastructure consumption

    Cloud-Native & Platform Engineering:

    • Design cloud-native, Kubernetes-native services
    • Work with DevOps/SRE on CI/CD, deployment automation, and scalability
    • Contribute to architecture decisions for multi-region, multi-cloud infrastructure
    • Improve monitoring, logging, and diagnostics

    Technical Leadership:

    • Lead architecture reviews and set engineering standards
    • Mentor engineers and guide complex problem-solving
    • Drive long-term roadmap for backend infrastructure and AI platform capabilities
    • Partner with Product, Runtime, and Infra leadership to translate requirements into scalable systems 

    Tech Stack (Indicative):

    • Languages: Golang (Primary), Python (Secondary)
    • Infrastructure: Kubernetes, Docker, Cloud (AWS/GCP/Azure)
    • Architecture: Microservices, gRPC, Event-driven systems
    • Data: SQL + NoSQL databases, caching, streaming systems
    • Observability: Prometheus, Grafana, OpenTelemetry (or similar)

    What You'll Need to Be Successful

    Core Engineering:

    • 5+ years of Backend or Infrastructure Engineering experience
    • Expert-level proficiency in Golang (must-have, heavy hands-on)
    • Strong experience building production-grade distributed systems
    • Proven track record on infrastructure platforms, PaaS, or deep-tech systems

    Infrastructure & Systems:

    • Deep understanding of cloud-native architectures and containerized environments
    • Strong experience with Kubernetes, Docker, and cluster orchestration
    • Familiarity with compute scheduling, resource management, or platform runtimes is a strong plus

    Databases & Data Systems:

    • Experience with distributed databases (PostgreSQL, Cassandra, DynamoDB, etc.)
    • Strong understanding of caching, queues, and streaming systems (Redis, Kafka, etc.)

    AI / Platform Exposure (Highly Preferred):

    • Experience on AI/ML platforms, model infrastructure, or data platforms
    • Familiarity with ML pipelines, inference systems, or GPU-backed workloads
    • Exposure to PyTorch, TensorFlow infrastructure, or model serving systems is a plus

    Ideal Candidate Profile (Who Will Thrive Here)

    • Infra-first backend engineers (not just API developers)
    • Background in AI infra, cloud platforms, developer platforms, or deep-tech systems
    • Strong systems thinkers who enjoy low-level performance, scalability, and architecture challenges
    • Startup-minded builders comfortable in ambiguous, high-ownership environments

    What We Offer

    • Competitive salary and benefits package
    • Work on cutting-edge AI infrastructure
    • Build products used by developers and enterprises
    • High ownership, fast execution, real impact
    • Collaborative, high-caliber team

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