Prompt Writer Jobs in New York (NOW HIRING)

Remote (US-Based) · Optional hybrid in New York, NY

LockedIn AI is the #1 real-time AI interview and meeting copilot, trusted by over one million users worldwide. We are a fast-growing company building the most advanced career preparation platform on the market.

Our platform delivers real-time, AI-powered assistance during live job interviews, coding assessments, and professional meetings — helping candidates communicate with clarity, confidence, and competence.

We are looking for a creative, technically sharp Prompt Engineer to design, craft, and optimize the prompts and instruction sets that power LockedIn AI’s core AI experience. This is a hands-on, high-leverage role — the quality of every AI-generated response our users see flows directly through your work.

You will own the full prompt lifecycle — from understanding user needs and model behavior, to writing and testing prompt architectures, to evaluating output quality and iterating based on real-world performance data. You will work across multiple LLM providers (OpenAI, Anthropic, open-source models) and develop prompt strategies that maximize accuracy, relevance, tone, and speed while minimizing hallucination, cost, and latency.

The ideal Prompt Engineer combines exceptional language skills with a deep, practical understanding of how large language models work. You think in systems — building reusable prompt templates, chain-of-thought architectures, and evaluation rubrics — not just one-off instructions. You are obsessive about output quality and relentless about testing and iteration.

• Design, write, and optimize production-grade prompts and system instructions that drive LockedIn AI’s real-time copilot across interview coaching, coding assistance, and meeting support use cases
• Develop and maintain prompt architectures including system prompts, few-shot examples, chain-of-thought reasoning, role-based instructions, and multi-turn conversation management
• Apply advanced prompt engineering techniques — including zero-shot, few-shot, chain-of-thought, self-consistency, tree-of-thought, and retrieval-augmented prompting — to maximize output quality for different product scenarios
• Build and maintain a structured prompt library and repository, documenting prompt patterns, version history, and performance benchmarks for reuse across the platform

• Design and execute rigorous prompt evaluation frameworks with clearly defined metrics — including accuracy, relevance, tone alignment, hallucination rate, response completeness, and latency
• Build and maintain benchmark datasets, golden answer sets, and scoring rubrics to systematically measure prompt performance across diverse user scenarios and edge cases
• Conduct systematic A/B tests and comparative experiments across prompt variations, model versions, and LLM providers to identify the highest-performing configurations
• Analyze prompt failure modes, identify patterns in low-quality outputs, and rapidly iterate on prompt designs to close quality gaps
• Work across multiple LLM providers (OpenAI, Anthropic, Google AI, open-source models) to understand model-specific behaviors, strengths, and limitations — and tailor prompt strategies accordingly
• Develop model routing logic and prompt adaptation layers that optimize for the best combination of quality, latency, and cost across different use cases and user segments
• Monitor and adapt prompts as models are updated or replaced, ensuring consistent output quality through model version changes and provider migrations
• Track and optimize token usage, prompt length, and inference costs — balancing response quality with sustainable unit economics

• Design prompts that effectively leverage retrieval-augmented generation (RAG) pipelines, ensuring AI responses are grounded in accurate, relevant, and up-to-date knowledge sources
• Develop context management strategies for real-time, multi-turn conversations — optimizing how conversation history, retrieved documents, and user context are structured within prompt context windows
• Collaborate with engineering to improve how retrieved content is formatted, ranked, and injected into prompts to maximize groundedness and minimize hallucination
• Test and optimize prompts under varying context window constraints, ensuring robust performance as conversation length and complexity increase

• Partner with product, engineering, research, and content teams to understand user needs, product requirements, and domain-specific language — translating them into effective prompt designs
• Collaborate with data and analytics teams to build feedback loops that connect real-world user interactions and quality signals back to prompt iteration cycles
• Document prompt engineering best practices, design patterns, and lessons learned — building organizational knowledge that scales beyond any single contributor
• Stay current on the latest developments in prompt engineering, LLM capabilities, and generative AI research — and proactively apply new techniques to improve LockedIn AI’s AI experience

• Ensure all prompts comply with LockedIn AI’s privacy-first design philosophy and user data handling guidelines
• Design safety guardrails, content filters, and fallback instructions within prompts to prevent harmful, biased, inappropriate, or off-topic AI outputs
• Test prompts against adversarial inputs, jailbreak attempts, and edge cases to identify and close safety vulnerabilities before they reach production
• Champion responsible prompt engineering practices — proactively addressing bias, fairness, and transparency in AI-generated content

• 2+ years of professional experience in prompt engineering, NLP, conversational AI, or a closely related role working hands-on with large language models in production
• Demonstrated experience designing and optimizing prompts for LLM-powered products or features — with measurable improvements in output quality, accuracy, or user satisfaction
• Hands-on experience with multiple LLM providers and APIs (OpenAI, Anthropic, Google AI, or open-source models) including deep familiarity with model-specific behaviors and limitations
• Experience building prompt evaluation frameworks, running systematic experiments, and using data to drive prompt iteration decisions
• Startup or high-growth environment experience preferred — comfort working in ambiguity and shipping fast

• Bachelor’s degree in Computer Science, Linguistics, Computational Linguistics, NLP, Data Science, or a related field.
• We value demonstrated prompt engineering skill, a strong portfolio, and practical results over credentials.

• Deep expertise in prompt engineering techniques including zero-shot, few-shot, chain-of-thought, self-consistency, role-based prompting, and retrieval-augmented prompting
• Strong understanding of how large language models work — including tokenization, context windows, temperature, top-p sampling, model limitations, and failure modes
• Proficiency in Python for prompt testing automation, evaluation scripting, and data analysis
• Experience with prompt management and evaluation tools (LangChain, LlamaIndex, Weights & Biases, Promptlayer, or similar)
• Familiarity with retrieval-augmented generation (RAG) architectures and how prompt design interacts with retrieved content
• Working knowledge of API integration, version control (Git), and basic data analysis (SQL, pandas)

• Language-first mindset: you have an exceptional command of language and understand that word choice, structure, and framing fundamentally change AI output quality
• Analytical rigor: you test systematically, measure precisely, and make prompt decisions based on data rather than intuition
• Creative problem-solving: you can approach the same problem from multiple angles, crafting unconventional prompt strategies when standard approaches fall short
• Strong written and verbal communication — you can document prompt architectures clearly, explain tradeoffs to cross-functional teams, and present evaluation results to non-technical stakeholders
• Self-starter mentality: you thrive with autonomy, move fast, and take ownership of prompt quality end-to-end

• Experience with real-time AI systems, conversational AI, or latency-critical prompt optimization
• Background in speech-to-text integration, multi-modal prompting, or real-time audio context handling
• Experience with agentic prompt architectures, tool-use prompting, or multi-step reasoning chains
• Familiarity with prompt security — including defense against prompt injection, jailbreaking, and adversarial prompt manipulation
• Background in linguistics, creative writing, journalism, or content strategy — bringing a language-native perspective to prompt design
• Experience in the career tech, edtech, or SaaS B2C space
• Contributions to open-source prompt engineering tools, published prompt research, or a public portfolio of prompt engineering work
• Prior startup founding or early employee experience (Seed to Series A stage)

Meaningful early-stage equity — be a true co-owner of what we're building

Your work directly powers a product used by 1M+ people worldwide

Join a lean, ambitious team where every individual matters

Remote-first culture with optional co-working in New York City

Be part of a bootstrapped rocket ship approaching its next growth phase

User-obsessed, feedback-driven, and built for speed

We pioneered the dual-layer AI copilot + human assist model for interviews — no one else has it.

The AI career tools space is exploding, and we’re the #1 rated platform with 1M+ users.

Every AI response our users see flows through your work — you directly control the intelligence and quality of the product experience.

Work across multiple frontier LLMs daily, experimenting with the latest models, techniques, and prompt architectures.

Prompt engineering is the single highest-leverage skill at an AI-native company — small changes in your work produce massive changes in product quality.

• Any relevant portfolio work, GitHub repos, or technical writing (optional but encouraged)

LockedIn AI is committed to building a diverse and inclusive team. We welcome applicants of all backgrounds, identities, and experiences. Employment decisions are made based on merit, qualifications, and business needs.