Founding Applied AI Engineer

Weekday (YC W21); San Francisco (CA); Hybrid; USD 220,000 - 300,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k)

Paid time off

Conferences & learning

Autonomy & ownership

Founders collaboration

Job summary

We are seeking a founding Applied AI Engineer to join Weekday in San Francisco. You will own AI product design and production, partnering with founders to identify high-impact opportunities and deliver 0→1 AI solutions.

With 5+ years in software/ML, you will build scalable AI systems, evaluate models, and shape the technical roadmap while mentoring junior engineers. This on-site/hybrid role offers strong ownership in a fast-moving startup.

Qualifications

• Bachelor's or Master's in CS/AI, or equivalent practical experience.
• 5+ years building software and ML systems.
• Experience deploying production AI applications.

Responsibilities

• Own the design and development of AI-powered products from concept through production.
• Work with founders and product leaders to identify high-impact AI opportunities.
• Build 0→1 AI applications, prototypes, and production systems.
• Design and implement LLM-powered applications, agents, and automation systems.
• Build and optimize RAG pipelines, embeddings, vector search, and context orchestration.
• Evaluate and integrate foundation models from providers or open-source ecosystems.
• Develop prompt engineering, model evaluation, and inference strategies.
• Build robust AI APIs, backend services, and production infrastructure.
• Develop evaluation frameworks to measure model quality, latency, reliability, and cost.
• Improve AI systems through experimentation, data analysis, feedback loops, and iteration.
• Collaborate with product/design teams to translate customer problems into AI experiences.
• Establish engineering best practices around testing, observability, deployment, and AI safety.
• Make architectural decisions enabling AI systems to scale.
• Help establish AI engineering standards, tooling, and technical roadmap.
• Mentor future AI/ML engineers as the team grows.
• Stay current with advances in LLMs, multimodal models, agents, reasoning systems, and applied AI research.

Skills

Python

ML engineering

Distributed systems

CI/CD

Docker

Kubernetes

Git

Problem solving

Communication

Team collaboration

Education

Bachelor's/Master's in CS/AI/Engineering

Tools

FastAPI

Flask

Terraform

PyTorch

LangChain

Job description

Location: San Francisco, CA
Experience: 5+ Years
Employment Type: Full-Time
Work Arrangement: On-site / Hybrid
Salary Range: $220,000 – $300,000 Base Salary

About the Role

We are looking for a highly motivated and entrepreneurial Founding Applied AI Engineer to join our early engineering team in San Francisco.

What You’ll Do

• Own the design and development of AI-powered products and features from concept through production.
• Work directly with founders and product leaders to identify high-impact opportunities for AI.
• Build 0→1 AI applications, prototypes, and production systems.
• Design and implement LLM-powered applications, AI agents, intelligent workflows, and automation systems.
• Build and optimize RAG pipelines, retrieval systems, embeddings, vector search, and context orchestration.
• Evaluate and integrate foundation models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems.
• Develop prompt engineering, model evaluation, fine-tuning, and inference strategies.
• Build reliable AI APIs, backend services, and production infrastructure.
• Develop evaluation frameworks to measure model quality, accuracy, latency, reliability, and cost.
• Improve AI systems through experimentation, data analysis, feedback loops, and continuous iteration.
• Work closely with product and design teams to transform customer problems into AI-powered experiences.
• Establish engineering best practices around testing, observability, monitoring, deployment, and AI safety.
• Make architectural decisions that enable AI systems to scale with the company.
• Help establish the company's AI engineering standards, tooling, and technical roadmap.
• Mentor future AI/ML engineers as the team grows.
• Stay current with advances in LLMs, multimodal models, agents, reasoning systems, and applied AI research.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related technical field, or equivalent practical experience.
• 5+ years of professional experience in software engineering, machine learning, AI engineering, or a related technical discipline.
• Strong proficiency in Python and modern software engineering practices.
• Demonstrated experience building and deploying production AI/ML systems.
• Strong understanding of machine learning fundamentals, model evaluation, experimentation, and optimization.
• Hands-on experience with LLMs and Generative AI applications.
• Experience building production applications using APIs from foundation-model providers or open-source models.
• Strong experience with cloud platforms such as AWS, GCP, or Azure.
• Experience with databases, APIs, distributed systems, and backend architecture.
• Strong understanding of Git, testing, CI/CD, Docker, and production deployment practices.
• Excellent problem-solving and debugging skills.
• Strong communication skills and the ability to work effectively in a highly collaborative environment.
• Ability to operate independently in an early-stage, fast-moving environment with ambiguity and changing priorities.

Preferred Qualifications

• Experience building AI agents and agentic workflows.
• Deep experience with RAG, vector databases, embeddings, semantic search, and information retrieval.
• Experience with LLM frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.
• Experience with model fine-tuning, distillation, inference optimization, or model serving.li>
• Experience with LLM evaluation, observability, and AI quality measurement.
• Experience with multimodal AI, NLP, computer vision, speech, or recommendation systems.
• Experience with Kubernetes, Terraform, Ray, Spark, or other distributed/cloud-native technologies.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, pgvector, or similar technologies.
• Experience building scalable backend systems using FastAPI, Flask, or similar frameworks.
• Experience working at a startup or building products from the ground up.
• Previous experience as an early engineering hire or founding engineer is highly desirable.
• Open-source contributions, published research, technical writing, or demonstrated AI projects are a plus.

Technical Environment

Languages: Python, SQL; JavaScript/TypeScript, Go, or C++ is a plus

AI/ML: PyTorch, TensorFlow, Scikit-learn, Hugging Face

Generative AI: LLMs, RAG, AI Agents, Prompt Engineering, Embeddings, Vector Search, Fine-Tuning, LLM Evaluation

Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, Terraform, CI/CD

Data: PostgreSQL, SQL, NoSQL, Vector Databases, Data Pipelines

AI Platforms: OpenAI, Anthropic, Google Gemini, open-source/foundation models

What We're Looking For

We are looking for someone who is more than a strong individual contributor. You should be a builder and owner.

You are comfortable moving between product discussions, writing code, experimenting with models, debugging production systems, and making architectural decisions.

You don't need every answer on day one. You should be curious, highly technical, comfortable with ambiguity, and excited to figure things out.

Most importantly, you should be excited about being one of the foundational engineers shaping an AI-first company.

Compensation & Benefits

• Base Salary: $220,000 – $300,000, depending on experience, technical expertise, and qualifications.
• Competitive performance bonus opportunities where applicable.
• Comprehensive medical, dental, and vision insurance.
• 401(k) or retirement savings program.
• Generous paid time off and company holidays.
• Professional development and learning opportunities.
• Company-sponsored conferences, courses, and technical resources.
• High degree of autonomy and ownership.
• Opportunity to work directly with founders and influence company strategy.
• Collaborative, high-growth environment in San Francisco.