Senior Applied AI Engineer

Quack is hiring a Senior Applied AI Engineer.

We’re a fast-growing startup tackling a huge market, trusted by global companies like Yotpo, Artlist, Notable, Rentman, and more.

We’re on a mission to keep every customer happy—building the next operating system for customer support teams. We’re well-funded, shipping fast, and delivering AI-powered products that customers actually love.

Who we are:

We value:

• Clear communication
• Deep focus
• A “keep it simple” mindset
• Ownership from end to end

Our founding team has worked together for 6+ years across multiple ventures. We care deeply about building elite product and tech teams and invest in the people we work with. We’re looking for sharp operators who want to grow fast.

About you:

You have:

• 5+ years of engineering experience (at least 3 years building distributed, scalable web applications)
• Strong communication and problem-solving skills
• A passion for delivering outstanding customer experiences

You’re familiar with:

• Transformer networks, attention mechanisms, and how they enable LLMs to generate responses and perform functions
• Prompt engineering techniques: chain-of-thought, static few-shot, dynamic few-shot
• Fine-tuning LLMs, optimizing training data, and mitigating bias
• Evaluation frameworks focused on performance, reliability, and bias
• Retrieval-Augmented Generation (RAG), semantic search, vector databases, and indexing strategies
• Full LLM architecture lifecycle: build, test, deploy, and scale
• Documenting development trade-offs and working with cloud infrastructure
• Balancing speed vs. quality while shipping real customer-facing features

Things you’ll do:

• Build AI feedback loops to capture user data and improve model performance
• Integrate LLMs into software products with scalable infrastructure
• Explore emerging LLM systems to drive measurable gains
• Design intuitive prompting strategies for automation
• Develop evaluation suites to monitor model performance
• Detect and resolve AI system failures or degradation
• Potentially implement LLM-assisted retrieval over large datasets
• Collaborate with Data and cross-functional teams to launch and refine features

Bonus:

• Experience with topic modeling and clustering techniques

What we offer:

Work your way:

• Work from home or in-office
• Flexible hours, manage your time independently

Taking care of your future self:

• Stock options plan
• Personal growth budget (for personal, not professional development)

Choose your stack:

• Latest MacBook Pro
• Home office equipment
• Personal budget to buy what you need

Looking after your present self:

• Paid vacation
• No work on holidays or holiday eves
• Wellness and mental health plan

Hiring process:

We move fast—from intro call to offer in 7 days.

• Send your CV to [email protected]
• Quick intro call with Aviram (CTO & hiring manager)
• Short home assignment to give you a feel for the work
• Deep-dive working session with Aviram and an engineer
• 1:1 with Nadav (CEO) to align on vision and strategy
• Provide 2–3 references
• Receive an offer 🙂

If this sounds like you or someone you'd highly recommend please reach out. We’d love to meet.