AI-Native Engineer – Full-Stack, Agentic AI Engineer

Job not on LinkedIn

🕒 July 27

🇵🇱 Poland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 30%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Vecten

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2010

🤖 Artificial Intelligence

🏥 Healthcare

💸 Finance

Artificial Intelligence • Healthcare • Finance

Vecten is an AI-native data and technology partner that builds proprietary data infrastructure and AI systems for private capital (venture capital and private equity) and healthcare & life sciences. It offers a full-stack delivery model — strategy workshops (Vecten Compass), an AI-native data platform deployed in client clouds (Vecten Core), an edge intelligence layer with ML models, LLM workflows and AI agents (Vecten Edge), and continuous operations with forward-deployed engineers and domain-specific AI agents (Vecten Drive). Vecten emphasizes compliant, production-ready systems (including HIPAA-aligned solutions for healthcare), measurable business outcomes, and long-term engineering partnerships; its clients collectively manage $1. 2T+ in assets and the company highlights ~15 years of engineering depth.

📋 Description

• Your primary goal is to build AI-powered infrastructure that gives VC and PE clients a genuine edge — proprietary systems that extract signals, automate decisions, and compound in value over time. • Agentic AI Systems: Multi-step LLM workflows, RAG pipelines, and agent orchestration systems — owned from architecture to production. From quick experiments to full production deployments — you know when to move fast and validate, and when to engineer for scale. Real clients depend on these systems to make investment decisions. • Full-Stack AI Applications: Client-facing web applications with AI embedded throughout — Python/FastAPI backends, React frontends, integrated with LLM providers (OpenAI, Anthropic, Gemini). Claude Code or Cursor is your primary environment. AI-assisted coding is your default mode, not a shortcut you reach for occasionally. • Data Platform Engineering: Scalable pipelines and cloud infrastructure (AWS/GCP) that underpin AI features — vector databases, data ingestion layers, API integrations. The foundation that makes everything else work. • Technical Discovery & Client Engagement: You’ll translate business needs into AI-first technical proposals — in the room with CFOs, GPs, and operating partners. You know what’s possible and you can explain it to someone who doesn’t write Python. • AI Quality & Internal Standards: Guardrails, automated testing, and observability for AI systems. You’ll help define what ‘good’ looks like across every engagement — contributing to internal engineering standards that compound over time.

🎯 Requirements

• Must-have: Proven, hands-on experience shipping production AI/LLM systems used by real users — not an internal demo or hackathon project. • Must-have: Advanced proficiency in an AI-native coding workflow — Claude Code, Cursor, Codex, or alternatives as your primary development environment, not a plugin you occasionally enable. • Expertise in at least one domain with broad proficiency across the entire stack (infrastructure, backend, data, frontend). Preferred stack: Terraform, Python, Snowflake, React. • Hands-on with LLM APIs, prompt engineering, RAG systems, and agentic frameworks (LangChain, LangGraph, CrewAI, Agno, or equivalent). • Strong spoken and written English — you communicate complex technical trade-offs clearly to both engineers and non-technical stakeholders. • Ability to run AI initiatives with limited support from our inhouse experts, from discovery to delivery, often across multiple client engagements in parallel. • Experience in fintech, private capital (VC/PE), or healthcare data systems is a strong plus. • Familiarity with data engineering stacks (Snowflake, dbt, Airflow, AWS data services) is a strong plus.

🏖️ Benefits

• Unrestricted AI Stack & Premium Gear: Fully paid licenses for Cursor, Claude Pro, etc. • Total Autonomy (Remote-First): No filler meetings, no Jira bloat, no micromanagement. You own the workflow. We care about shipped systems in production, not logged hours. • Direct Impact: You’ll work face-to-face with our CEO, CTO & VPs and VC/PE General Partners. • Frontier Engineering Culture: Build alongside elite engineers who are shipping systems that drive real investment decisions. Backed by continuous growth and a strong knowledge-sharing culture (check our YouTube).