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

We’re hiring a Backend AI Engineer to design and build the backbone of intelligent systems — from LLM orchestration to inference pipelines and distributed APIs.

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.