Artificial Intelligence Engineer

0 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Company Description


Vasco Tech is an AI-driven technology company focused on building transformative solutions across industries. Our mission is to harness the power of artificial intelligence to redefine how people learn, work, and innovate. With a vision rooted in progress and impact, we are creating tools and platforms that push the boundaries of what’s possible. We’re not just building technology - we’re shaping the future.


Role Description


Backend AI Engineer

You’ll architect the backend infrastructure, implement reasoning workflows, and optimize for scale, speed, and reliability.

You’ll work closely with the founding team to develop next-generation AI systems that think, adapt, and self-optimize.


Key Responsibilities


  • Architect and develop

    high-performance backend systems

    for AI orchestration, data retrieval, and reasoning.
  • Build and optimize

    LLM inference pipelines

    and

    multi-model integration layers

    .
  • Implement

    retrieval-augmented generation (RAG)

    ,

    context management

    , and

    memory systems

    .
  • Design

    APIs and microservices

    (REST / GraphQL) for reasoning and model coordination.
  • Manage

    data storage and vector databases

    (Qdrant / Pinecone / Postgres / Neon).
  • Build

    asynchronous, event-driven pipelines

    to handle large-scale requests and model calls.
  • Deploy and maintain

    scalable infra

    using AWS, Docker, and CI/CD pipelines.
  • Implement

    observability tools

    ,

    evaluation metrics

    , and

    reasoning trace systems

    for debugging and improvement.
  • Continuously benchmark and integrate

    new open-source or proprietary models

    .

Must-Have Skills


  • Strong in

    Python

    (FastAPI, asyncio, multiprocessing, or similar frameworks).
  • Proficient in

    Node.js / TypeScript

    for service integration.
  • Deep understanding of

    API design

    ,

    scalable microservices

    , and

    async pipelines

    .
  • Hands-on experience with

    vector databases

    (Qdrant, Pinecone, Weaviate) and

    Postgres / Neon

    .
  • Practical understanding of

    LLM APIs

    (OpenAI, Anthropic, Mistral, etc.) and

    RAG architectures

    .
  • Strong fundamentals in

    data structures

    ,

    caching

    ,

    concurrency

    , and

    distributed systems

    .
  • Experienced with

    Docker

    ,

    AWS / Vercel

    , and

    CI/CD

    automation.
  • Ability to

    debug complex backend systems

    across data, infra, and AI layers.

Preferred Skills


  • Knowledge of

    LangChain

    ,

    LlamaIndex

    , or custom orchestration logic.
  • Experience with

    agentic workflows

    ,

    model routing

    , or

    self-evaluating pipelines

    .
  • Familiarity with

    model fine-tuning

    ,

    embedding optimization

    , or

    vector search ranking

    .
  • Exposure to

    observability stacks

    (Langfuse, Posthog, Sentry).
  • Contributions to

    open-source AI infrastructure

    or published repos.
  • Background in

    distributed system design

    or

    cloud-native architecture

    .

Mindset & Culture Fit


  • Builder-first

    — comfortable owning systems from architecture to deployment.
  • Systems thinker

    — sees the interdependencies between models, data, and orchestration logic.
  • Bias for speed and learning

    — iterates fast and optimizes later.
  • Detail-obsessed

    — balances performance with correctness and traceability.
  • Autonomous

    — thrives without constant direction, takes full ownership.

Compensation & Growth

  • Competitive salary.
  • Opportunity to own

    core AI infrastructure and reasoning pipelines

    .
  • Direct collaboration with the founding team on high-impact architecture decisions.


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