AI Product Architect In Office (Austin, TX)

Dover; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

S27a is seeking an AI Product Engineer to bridge cutting-edge AI with real healthcare needs in Austin, TX. You will spend time on prompt design, product strategy, testing new AI features, and translating client requirements into launchable solutions.

As the platform grows, you will test multi-agent architectures, evaluate models, and run A/B tests on conversation flows to ship next week’s lightweight bot ideas.

Qualifications

• 3–5 years in product management, AI/ML engineering, or technical product roles.
• Advanced experience with LLMs, prompt engineering, and AI model evaluation.
• Track record of taking products from concept to launch, preferably in fast-paced environments.
• Experience with lean startup methodologies, hypothesis-driven development, and MVP scoping.
• Strong analytical skills with ability to design experiments and interpret results.

Responsibilities

• Design and optimize prompts for complex healthcare workflows including multi-agent systems, appointment scheduling, and patient engagement flows.
• Collaborate with engineering to implement and test new AI architectures, models, and conversational AI features.
• Run experiments comparing different models, prompt strategies, and conversation approaches.
• Build prompt evaluation frameworks and testing pipelines that scale across multiple healthcare use cases.
• Translate ambitious client requirements into lean MVPs that can be launched and iterated quickly.
• Create product hypotheses and validation frameworks for new AI features and healthcare use cases.
• Scope complex multi-agent workflows into phases that minimize risk while maximizing learning.
• Partner with clients to identify the core problem beneath their feature requests.
• Serve as primary user of our internal AI agent platform, stress-testing new features and identifying improvement opportunities.
• Design and execute end-to-end testing for new AI capabilities, model deployments, and platform releases.
• Create testing scenarios that cover edge cases, failure modes, and integration points.
• Establish metrics and monitoring systems for conversation quality, model performance, and user satisfaction.
• Work closely with engineering team to prioritize AI/ML platform features and improvements.
• Identify opportunities to leverage new AI technologies (advanced prompting techniques, RAG improvements, model fine-tuning).
• Drive roadmap decisions based on client feedback, platform usage data, and emerging AI capabilities.
• Communicate technical AI concepts to non-technical stakeholders and clients.

Skills

Product management

AI/ML engineering

Technical product roles

Lean startup

Experiment design

A/B testing

Data-driven decisions

LLMs

Prompt engineering

Model evaluation

Tools

AI/ML frameworks

LLMs

Prompt engineering

Model evaluation

Job description

About the Role

We're looking for an AI Product Engineer who can bridge the gap between cutting-edge AI capabilities and real healthcare needs. You'll spend 40%+ of your time crafting and optimizing prompts while driving product strategy, testing new AI features, and translating complex client requirements into lean, launchable solutions.

As our platform grows, you'll be the first to test multi-agent architectures, evaluate new models, and identify which AI innovations actually move the needle for patient outcomes. You're equally comfortable running A/B tests on conversation flows and scoping down a client's ambitious bot idea into something we can ship next week.

What You'll Do

Core Prompt Engineering & AI Implementation (40%+)

• Design and optimize prompts for complex healthcare workflows including multi-agent systems, appointment scheduling, and patient engagement flows

• Collaborate with engineering to implement and test new AI architectures, models, and conversational AI features

• Run experiments comparing different models, prompt strategies, and conversation approaches

• Build prompt evaluation frameworks and testing pipelines that scale across multiple healthcare use cases

Product Strategy & Client Requirements

• Translate ambitious client requirements into lean MVPs that can be launched and iterated quickly

• Create product hypotheses and validation frameworks for new AI features and healthcare use cases

• Scope complex multi-agent workflows into phases that minimize risk while maximizing learning

• Partner with clients to identify the core problem beneath their feature requests

Platform Testing & Quality Assurance

• Serve as primary user of our internal AI agent platform, stress-testing new features and identifying improvement opportunities

• Design and execute end-to-end testing for new AI capabilities, model deployments, and platform releases

• Create testing scenarios that cover edge cases, failure modes, and integration points

• Establish metrics and monitoring systems for conversation quality, model performance, and user satisfaction

Technical Product Management

• Work closely with engineering team to prioritize AI/ML platform features and improvements

• Identify opportunities to leverage new AI technologies (advanced prompting techniques, RAG improvements, model fine-tuning)

• Drive roadmap decisions based on client feedback, platform usage data, and emerging AI capabilities

• Communicate technical AI concepts to non-technical stakeholders and clients

What You Bring

Required Experience

• 3-5 years in product management, AI/ML engineering, or technical product roles

• Advanced experience with LLMs, prompt engineering, and AI model evaluation

• Track record of taking products from concept to launch, preferably in fast-paced environments

• Experience with lean startup methodologies, hypothesis-driven development, and MVP scoping

• Strong analytical skills with ability to design experiments and interpret results

Technical Requirements

• Hands-on experience with AI/ML frameworks, APIs, and model comparison

• Understanding of conversational AI architecture, multi-agent systems, and prompt optimization techniques

• Ability to work with engineering teams on technical implementation and system design

• Experience with A/B testing, metrics analysis, and data-driven product decisions

Preferred Qualifications

• Background in healthcare technology or regulated industries

• Experience with AI safety, model alignment, or responsible AI practices

• Familiarity with software development processes and platform architecture

• Previous experience as a power user or early adopter of AI tools and platforms

Growth Opportunities

You'll develop deep frontlines understanding of conversational AI architecture, multi-agent systems, and prompt optimization techniques. This goes beyond hackathons and GitHub repos to agents that work in the real world on hundreds of real patients. You'll get front-row access to cutting-edge LLM failure modes that few people globally get to observe—understanding why agents break in production and building systems that consistently work for real healthcare interactions.

Location & Team

• Austin, TX

• Work closely with the GM, Agent Platform and Product who somehow convinced therapists to teach her about patient communication (they're probably regretting it). Obsessed with measuring whether AI can actually be funny AND helpful. Builds modular systems because apparently even empathy needs to scale.

• As the primary user of our platform, you'll have direct influence on engineering priorities and product direction without needing formal authority

We're building AI that actually works in the messy reality of healthcare. If you love turning AI possibilities into practical solutions, let's talk.