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: (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.,(Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.,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
Senior AI Engineer (YC Startup) – Product-Focused & Client-Facing
US / Remote - With Offices in NY
Full-Time
Est. Fee
$13,500 - 18,750
Salary Range
$180,000 - $250,000 per year
Contract
7.5% of Salary, 60 day guarantee
Job Details
Job Overview
This role centers on building and optimizing advanced AI-driven systems that bring agentic workflows to life. You’ll design and implement LLM-powered pipelines with continuous evaluation and feedback loops, develop organization-specific customization layers, and create engaging voice- and message-based agents. Beyond deep technical execution, you’ll collaborate closely with product teams, stakeholders, and users to shape product direction and translate real-world needs into scalable solutions. With expertise in machine learning and production AI systems (RAG, vector search, prompt engineering) and strong Rails proficiency, you’ll architect reliable infrastructure that integrates seamlessly into complex environments. The ideal candidate is both an innovative builder and a clear communicator, able to thrive in ambiguity, adapt quickly to new frameworks, and deliver impactful, enterprise-grade AI solutions at speed.
Responsibilities
Responsibilities
As a Senior AI Engineer, you’ll play a foundational role in shaping Arist’s next generation of AI-driven products. This is not a purely heads-down engineering role — in addition to designing and shipping advanced agentic systems, you’ll collaborate directly with product teams, founders, and users to shape product direction and turn feedback into production-grade technical solutions. Your work will bridge deep technical execution with thoughtful communication and iteration.
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
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).
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.
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.
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.
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.
Ideal Candidate
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.
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
1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.
2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.
3. 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.
Common Rejection Reasons
Experience Level: The candidate demonstrates mid-level experience signals but the role requires senior or staff-level impact and ownership across full product lifecycle.
Startup Experience: The candidate has primarily worked at larger organizations and lacks recent startup experience (preferably at companies with $7M–$8M ARR or similar stage).
Enterprise Exposure: The candidate has not worked on products selling to enterprise customers, which is a core requirement for Arist's product environment.
Culture Fit: The candidate may not align with Arist’s culture emphasizing caring, kindness, ambition, adaptability, and high learning agility.
Communication & Collaboration: The candidate did not demonstrate strong product sense or ability to communicate effectively with customers, clients, or cross-functional teams.
Compensation: The candidate’s expected salary exceeds the range for this role given their experience and impact level.
Location: The candidate does not reside within the U.S. or in a commutable time zone and is not open to relocation.
Interest Alignment: The candidate expressed limited interest in user-facing or customer-interacting aspects of the role, which are essential for success at Arist.
These are common reasons why candidates have been rejected for this position. Consider these when selecting candidates to submit.
About the Company
Company Overview
Company Size: 30
Industry: AI-enabled microlearning, enterprise Learning & Development (L&D), and edtech
Arist is growing ~4x YoY, will hit ~$10M ARR and be profitable by EOY, has zero competitors, is a lean team of 18, and pays exceptionally well. Arist is building end-to-end agents to replace HR and Training teams and make learning 10x better. Clients include Microsoft and Novartis.
Arist began with a bold vision: to deliver entrepreneurship education to high school students in conflict zones through text messages—meeting learners where they already were, even without internet or laptops. From that origin, Arist has grown into a full-stack, AI-powered enablement platform that helps enterprises deliver training, nudges, surveys, and communications seamlessly through SMS, Slack, Microsoft Teams, WhatsApp, email, and more.
Our “push-based” model bypasses traditional LMS systems to meet employees where attention already lives. Today, Arist powers mission-critical learning and enablement for global enterprises, bridging the gap between intent and action through AI agents that handle need analysis, content creation, delivery, and analytics at scale.
Company Culture
Arist’s culture is rooted in mission, pragmatism, and impact. We believe learning should be frictionless, embedded in daily workflows, and designed for real-world results. Our team values thoughtful, asynchronous communication (memo-driven), rapid iteration powered by AI, and uncompromising standards of enterprise reliability.
Rather than buzzwords, our culture is defined by outcomes: a relentless focus on solving measurable business problems, empowering teammates to think independently, and building with agility and purpose.
Benefits
Retirement/401k
Health Insurance
Vision Insurance
Dental Insurance
US citizen/visa only
Relocation & Sponsorship
Relocation Assistance
Visa Sponsorship
What you can expect
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
This is a founding-level role with significant opportunities for advancement. You’ll have the chance to:
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.
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.
Companies to Source From
These companies are similar to our client. Candidates with experience at these companies are seen as a big plus.
Openaiopenai.com
Anthropicanthropic.com
Huggingfacehuggingface.co
Coherecohere.com
Mistralmistral.ai
Stabilitystability.ai
Scalescale.com
Wandbwandb.ai
Modularmodular.com
Togethertogether.ai
Octomloctoml.ai
Pineconepinecone.io
Runwaymlrunwayml.com
Jasperjasper.ai
Copycopy.ai
Tometome.app
Perplexityperplexity.ai
Adeptadept.ai
Inflectioninflection.ai
Typefacetypeface.ai
Gleanglean.com
Notionnotion.so
Grammarlygrammarly.com
Replitreplit.com
Githubgithub.com
Charactercharacter.ai
Elevenlabselevenlabs.io
Descriptdescript.com
Googlegoogle.com
Microsoftmicrosoft.com
Metameta.ai
Appleapple.com
Databricksdatabricks.com
Snowflakesnowflake.com
Servicenowservicenow.com
Salesforcesalesforce.com
Adobeadobe.com
Shopifyshopify.com
Stripestripe.com
Linkedinlinkedin.com
Client Messaging Channel
Client Messaging Channel
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Login & Apply to View More
Sign in to your account to access full job details and apply.
Common Rejection Reasons
Experience Level: The candidate demonstrates mid-level experience signals but the role requires senior or staff-level impact and ownership across full product lifecycle.
Startup Experience: The candidate has primarily worked at larger organizations and lacks recent startup experience (preferably at companies with $7M–$8M ARR or similar stage).
Enterprise Exposure: The candidate has not worked on products selling to enterprise customers, which is a core requirement for Arist's product environment.
Culture Fit: The candidate may not align with Arist’s culture emphasizing caring, kindness, ambition, adaptability, and high learning agility.
Communication & Collaboration: The candidate did not demonstrate strong product sense or ability to communicate effectively with customers, clients, or cross-functional teams.
Compensation: The candidate’s expected salary exceeds the range for this role given their experience and impact level.
Location: The candidate does not reside within the U.S. or in a commutable time zone and is not open to relocation.
Interest Alignment: The candidate expressed limited interest in user-facing or customer-interacting aspects of the role, which are essential for success at Arist.
These are common reasons why candidates have been rejected for this position. Consider these when selecting candidates to submit.
Relocation & Sponsorship
Relocation Assistance
Visa Sponsorship
Must-Have 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
1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.
2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.
3. 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.
Benefits
Retirement/401k
Health Insurance
Vision Insurance
Dental Insurance
US citizen/visa only
Login & Apply to View More
Sign in to your account to access full job details and apply.
Companies to Source From
These companies are similar to our client. Candidates with experience at these companies are seen as a big plus.
Openaiopenai.com
Anthropicanthropic.com
Huggingfacehuggingface.co
Coherecohere.com
Mistralmistral.ai
Stabilitystability.ai
Scalescale.com
Wandbwandb.ai
Modularmodular.com
Togethertogether.ai
Octomloctoml.ai
Pineconepinecone.io
Runwaymlrunwayml.com
Jasperjasper.ai
Copycopy.ai
Tometome.app
Perplexityperplexity.ai
Adeptadept.ai
Inflectioninflection.ai
Typefacetypeface.ai
Gleanglean.com
Notionnotion.so
Grammarlygrammarly.com
Replitreplit.com
Githubgithub.com
Charactercharacter.ai
Elevenlabselevenlabs.io
Descriptdescript.com
Googlegoogle.com
Microsoftmicrosoft.com
Metameta.ai
Appleapple.com
Databricksdatabricks.com
Snowflakesnowflake.com
Servicenowservicenow.com
Salesforcesalesforce.com
Adobeadobe.com
Shopifyshopify.com
Stripestripe.com
Linkedinlinkedin.com
Senior AI Engineer (YC Startup) – Product-Focused & Client-Facing - Bounty Position
Company: Arist
Location: US / Remote - With Offices in NY
Employment Type: Full-Time
Salary: $180,000 - $250,000 per year
Bounty Amount: $13,500 - 18,750
This role centers on building and optimizing advanced AI-driven systems that bring agentic workflows to life. You’ll design and implement LLM-powered pipelines with continuous evaluation and feedback loops, develop organization-specific customization layers, and create engaging voice- and message-based agents. Beyond deep technical execution, you’ll collaborate closely with product teams, stakeholders, and users to shape product direction and translate real-world needs into scalable solutions. With expertise in machine learning and production AI systems (RAG, vector search, prompt engineering) and strong Rails proficiency, you’ll architect reliable infrastructure that integrates seamlessly into complex environments. The ideal candidate is both an innovative builder and a clear communicator, able to thrive in ambiguity, adapt quickly to new frameworks, and deliver impactful, enterprise-grade AI solutions at speed.
