Prompt Engineer / AI Engineer at HyperFi

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

18 Apr, 26

Salary

0.0

Posted On

18 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Prompt Engineering, AI Engineering, LangChain, PySpark, Databricks, Python, RAG, Model Evaluation, Observability, Feedback Loops, Agent Workflows, Context Construction, Telemetry, Collaboration, Testable Code, Maintainable Code

Industry

Software Development

Description

We're looking for a Prompt Engineer / AI Engineer to join early. Someone who knows how to move from prototype to production, who can design prompts, evaluate them, and wrap them in real workflows that run reliably. You’ll work closely with the CTO and Tech Lead to build intelligent systems that plug into a larger product — not just toy demos. If you’re fluent in RAG, LangChain, and PySpark, and care about real-world agent behavior, this is your kind of role. 💥 What You’ll Do Build agentic LLM pipelines using LangChain, LangGraph, and LangSmith Design and iterate on prompt strategies, with a focus on consistency and context Construct retrieval-augmented generation (RAG) systems from scratch Own orchestration of PySpark and Databricks workflows to prepare inputs and track outputs Instrument evaluation metrics and telemetry to guide prompt evolution Work alongside product, frontend, and backend engineers to tightly integrate AI into user-facing flows 🧰 Tech Stack (So Far) Python (primary language for all LLM + orchestration work) LangChain + LangGraph + LangSmith Databricks + PySpark for processing, labeling, and training context Gemini + model routing logic Postgres, and custom orchestration via MCP GitHub Actions, GCP There’s enough here to move fast, but still plenty of room for your fingerprints. 💻 How We Build Engineers come first: your time, focus, and judgment are respected Deep work > chaos: fixed cycles & cooldowns protect focus and keep context switching low Autonomy is the default: trusted builders who own outcomes, no babysitters Ship daily, safely: merge early, integrate vertically, ship often, use feature flags, and keep momentum Outcomes over optics: solve real problems, not ticket soup Voice matters: from week one, contribute, improve something, and shape how we build Senior peers, no ego: collaborate in a high-trust, async-friendly environment Bold problems, cool tech: work on complex challenges that actually move the needle Fun is part of it: we move fast, but we also celebrate wins and laugh together ✅ What We’re Looking For 5–7 years building production-grade ML, data, or AI systems Strong grasp of prompt engineering, context construction, and retrieval design Comfortable working in LangChain and building agents, not just chains Experience with PySpark and Databricks to handle real-world data scale Ability to write testable, maintainable Python with clear structure Understanding of model evaluation, observability, and feedback loops Excited to push from prototype → production → iteration Confident English skills to collaborate clearly and effectively with teammates 🔥 Bonus If You: Have built agent-like workflows with LangGraph or similar Have worked on semantic chunking, vector search, or hybrid retrieval strategies Can walk us through a real-world prompt failure — and how you fixed it Have contributed to OSS tools or internal AI platforms Think of yourself as both an engineer and a systems designer 📍 Location & Compensation Must be based in San Francisco, Las Vegas, or Tel Aviv Full-time role with competitive comp Flexible hours, async-friendly culture, engineering-led environment

Responsibilities

You will build agentic LLM pipelines and design prompt strategies while constructing retrieval-augmented generation systems. Additionally, you will own orchestration of workflows and work closely with other engineers to integrate AI into user-facing flows.