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    Home/Jobs/Software Engineer, AI Squads

    Software Engineer, AI Squads

    Telnyx

    Hanoi / Bengaluru / Ho Chi Minh
    3-5 years
    Today
    ₹13–25 LPA
    Full-time
    Onsite

    Skills Required

    Transformers
    vLLM
    Retrieval Augmented Generation (RAG) systems
    LLM
    LLM optimization techniques
    async programming
    concurrency
    parallel execution
    microservice-based systems
    PyTorch
    DeepSpeed
    Ray
    Docker
    Kubernetes
    Prometheus

    Description

    Telnyx is an industry leader building the future of global connectivity. We're seeking a Software Engineer for our AI Squads to develop platforms, services, and tooling supporting AI-powered products.

    Company: Telnyx

    Role: Software Engineer, AI Squads

    Location: Hanoi, Vietnam; Ho Chi Minh, Vietnam; Bangalore, India

    Experience:

    • Experience with microservice-based systems
    • Strong understanding of async programming, concurrency, and parallel execution
    • Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date)

    Key Skills:

    • async programming
    • concurrency
    • parallel execution
    • microservice-based systems
    • cloud-native technologies

    Role Focus:

    • Build, test, and deploy scalable microservices for AI-powered systems
    • Design developer-friendly APIs, agents and internal tools
    • Contribute to AI inference, embeddings, and platform services
    • Optimize performance, reliability, and observability in production environments
    • Collaborate closely with Product, Infrastructure, and ML teams
    • Troubleshoot, debug, and support critical systems running in production
    • Participate in code reviews and uphold high engineering and operational standards

    Nice to have:

    • Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
    • Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
    • Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
    • Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
    • Background in Retrieval Augmented Generation (RAG) systems

    Other:

    • Our AI Chapter is made up of multiple squads
    • We hire into a shared AI engineering pipeline
    • Final squad alignment happens later, based on strengths and interests, team needs, and where you’ll have the biggest long-term impact
    • You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Generative AI with Large Language Models

    Coursera

    Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

    Large Language Models: Application through Production

    edX

    Production-focused LLM course covering deployment, monitoring, and scaling.

    Deep Neural Networks with PyTorch

    Coursera

    Hands-on PyTorch from tensors to CNNs and transfer learning.

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