Senior AI Engineer (YC Startup) – Product-Focused & Client-Facing
Bounty Amount: $13,500 - 18,750
Company Name: Arist
Role Type: Full-Time
Location: US / Remote - With Offices in NY
Salary / Hourly Rate: $180,000 - $250,000 per year
Benefits: US citizen/visa only
Role Information
Role Overview: N/A
Responsibilities: Design and implement agentic workflows powered by LLMs for real-world task execution., Build customization layers tailored to organization-specific logic and requirements., Collaborate directly with product teams, founders, and users to understand pain points, shape product direction, and iterate quickly on prototypes., Translate user and product feedback into scalable, production-grade technical solutions., Develop voice-based and message-based learning agents that drive engagement, incorporating evaluation, feedback loops, and continuous monitoring., Architect AI pipelines (RAG, prompt engineering, evaluation) and build reliable infrastructure that integrates into complex environments., Clearly communicate technical decisions to both technical and non-technical stakeholders, ensuring alignment across teams., Manage multi-agent orchestration and core AI system infrastructure.
Qualifications: Machine Learning Expertise
5+ years of experience in ML (PyTorch, TensorFlow).
2+ years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic)., 5+ years of experience in ML (PyTorch, TensorFlow)., 2+ years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic)., AI System Development
Proven experience building and deploying production AI systems, including RAG and vector search.
Knowledge of prompt engineering, AI safety, and content filtering best practices.
Comfort architecting scalable infrastructure that integrates into complex environments., Proven experience building and deploying production AI systems, including RAG and vector search., Knowledge of prompt engineering, AI safety, and content filtering best practices., Comfort architecting scalable infrastructure that integrates into complex environments., Technical Proficiency
Familiarity with Rails is a plus, but not required — strong candidates can ramp up quickly.
Experience working with REST APIs, PostgreSQL, ActiveRecord, and RSpec.
Understanding of frameworks like LangChain or LlamaIndex, or the ability to learn them rapidly., Familiarity with Rails is a plus, but not required — strong candidates can ramp up quickly., Experience working with REST APIs, PostgreSQL, ActiveRecord, and RSpec., Understanding of frameworks like LangChain or LlamaIndex, or the ability to learn them rapidly., Communication & Collaboration
Proven ability to engage directly with users, customers, and cross-functional teams to gather feedback and shape technical solutions.
Comfortable explaining complex concepts clearly to both technical and non-technical stakeholders.
Experience collaborating with product and design teams to align on goals and iterate quickly.
Strong written and verbal communication skills., Proven ability to engage directly with users, customers, and cross-functional teams to gather feedback and shape technical solutions., Comfortable explaining complex concepts clearly to both technical and non-technical stakeholders., Experience collaborating with product and design teams to align on goals and iterate quickly., Strong written and verbal communication skills., Builder Mindset
Thrives in ambiguity, learns quickly, and iterates fast in lean environments.
Excited to work in a small, high-impact team where communication and ownership are key., Thrives in ambiguity, learns quickly, and iterates fast in lean environments., Excited to work in a small, high-impact team where communication and ownership are key.
Minimum Requirements: 5+ years of experience in Machine Learning (PyTorch, TensorFlow).,2+ years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic).,Proven track record of building and deploying production AI systems, including RAG and vector search.,Strong understanding of AI safety, prompt engineering, and content filtering best practices.,Excellent communication skills, with experience collaborating directly with users, clients, or cross-functional teams.,Familiarity with Rails is a plus, but not required — strong candidates can ramp up quickly.
Screening Questions: Please share a 2–3 minute video (screen share + voice) walking us through something you’ve built or worked on recently — ideally related to AI, LLMs, or system integration. This is a hard requirement, we cannot move forward with your application without it.,Please share a link to your GitHub or personal portfolio (if applicable):,Are you comfortable building with AI hands-on and working directly with customers to gather feedback, shape features, and help launch new products? Please share an example of when you’ve done this or how you would approach it.
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: Initial Call (30 min) – Introductory conversation with a recruiter or founder to review background, motivations, and role fit.Technical Deep Dive (60–90 min) – Live discussion with senior engineers covering LLM design scenarios, Rails integration, and system-level problem solving.Practical Exercise / Case Study – Short take-home or live coding assignment focused on building or evaluating an AI workflow.Final Round (60 min) – Cultural and cross-functional interviews with founders/team to assess collaboration, communication, and alignment with mission.
Day to day: You’ll spend your days designing, building, and shipping AI systems that deliver immediate real-world impact. Your time will be split between hands-on development (Rails, ML/LLM workflows), collaborating with founders and engineers to shape product direction, and rapidly iterating on prototypes based on real feedback. Most days blend deep technical work with fast feedback loops from both internal stakeholders and enterprise clients, giving you direct visibility into how your work moves the product forward.
Team: You’ll join a lean, highly technical founding team, reporting directly to the CTO and collaborating closely with the CEO and product leads. The team is composed of engineers with backgrounds in AI/ML, backend systems, and enterprise software, all focused on building production-grade AI enablement tools. You’ll have significant ownership and autonomy, with the ability to shape architecture, standards, and culture.
Growth: Own core technical systems from day one., Mentor and grow future engineers as the team scales., Influence product strategy at both the technical and business levels., Build a track record of shipping AI systems at scale — positioning yourself for leadership roles within Arist or in future ventures.
Ideal Candidate Profile: Innovative Builder — Designs and optimizes sophisticated AI workflows that solve real enterprise challenges, from ideation to deployment., Product-Minded Communicator — Excels at working directly with users, clients, and cross-functional teams to gather feedback and translate it into scalable technical solutions. Comfortable navigating both technical deep dives and high-level product conversations., Technically Excellent — Brings strong expertise in Rails (REST APIs, PostgreSQL, ActiveRecord, RSpec) and hands-on experience deploying scalable AI systems using modern frameworks and infrastructure., Collaborative and Fast-Moving — Thrives in ambiguity, learns new frameworks (LangChain, LlamaIndex, etc.) quickly, and delivers results at startup speed. Works seamlessly with founders, engineers, and product teams to iterate rapidly., Examples of Candidates (do not contact)
Yutong Xue
Andrew R. Reed
Zion Badash
Ryan Rishi, Yutong Xue, Andrew R. Reed, Zion Badash, Ryan Rishi
