Artificial Intelligence Engineer

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.