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AI Prompt Engineer

Chicago,...
B

Builtin

Startup
Category
Technical
Experience
0-3 years
Type
Full-Time
Location
Chicago, Illinois, USA;...
Job Description
Benefits & Culture
Flexible hours
Remote work
Paid time off
Fast-paced environment
Direct feedback
Growth opportunities
This goes straight to the founder
Share on: TwitterFacebookLinkedInHacker NewsReddit

No recruiters. Founders reply directly.

Founder Signals
Response Rate
85%
Avg Response Time
2 hours
Compensation Calculator
In startups, higher salary usually means lower equity.
Salary (affects equity %)
Link salary ↔ equity
$125,000
$80,000$200,000
Equity % (auto from trade-off model)
0.93%
0%5%
Projected Exit Value
$350,000,000
$10M$500M
Live Trade-off
Salary
Equity %
Est. Equity Value at Exit
$100,000
1.08%
$1,884,167
$125,000
0.93%
$1,636,250
$150,000
0.79%
$1,388,333
$175,000
0.65%
$1,140,417

Advanced Salary & Equity Calculator

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Responsibilities:

  1. Design, test, and maintain reusable prompt templates for enterprise LLM use cases.
  2. Run A/B tests and collaborate with trainers and integrators to embed prompts into RAG and AI workflows.
  3. Keep prompt libraries updated with best practices and client guidelines.

Core Responsibilities:

  1. Lead design and standards for LLM-based applications, including prompt and agent architectures, retrieval-augmented pipelines, evaluation frameworks, safety guardrails, developer tooling, and mentoring.
  2. Drive model collaboration, red-teaming, performance trade-offs, and documentation for organization-wide reuse.

Additional Responsibilities:

  1. Design, build, and maintain production-ready AI solutions, automations, and system integrations.
  2. Analyze workflows, implement secure RAG and AI assistants, develop API/webhook integrations, build internal apps and dashboards, ensure HIPAA-compliant data handling, monitor quality, test and document systems, and drive cross-functional adoption and measurable operational outcomes.
  3. Lead and establish AQM Prompt Engineering practices: define methodology and standards, build reusable prompt libraries, mentor a small team, lead complex customer engagements, validate prompts with sampling and precision/recall analysis, collaborate with product and pre-sales, and deliver training and enablement for prompt-driven QM deployments.
  4. Design, author, and iteratively optimize LLM evaluation prompts; define evaluation scope and pass/fail criteria with customers; select and analyze call samples; measure precision/recall; maintain a versioned prompt library; collaborate with QA and implementation teams; debug prompt failures; develop standards, templates, and support pre-sales demonstrations.
  5. Lead the identification of AI opportunities, design and refinement of prompts and AI-enabled workflows, prototyping and validation of AI outputs, user training, use case documentation, and coordination of deployment and integration efforts to improve operational efficiency.
  6. Design and implement conversational AI systems, manage prompt orchestration, and ensure conversational quality through advanced evaluation frameworks.
  7. Design, optimize, and iterate multi-turn conversational flows for text and voice agents.
  8. Craft persona-driven prompts and multilingual templates, test with recordings and simulations, analyze live interactions to reduce hallucinations and improve tone, and collaborate with PMs and engineers to integrate prompts, maintain a versioned prompt library, and ensure compliance and privacy.