Prompt Engineer & AI Optimization Specialist

Building Next-Gen Self-Improving AI for Sales & Marketing Automation

We’re a fast-growing startup developing an AI-driven sales and marketing automation platform. Our solution helps clients identify and engage their Ideal Customer Profiles (ICPs) through both text-based and voice-based interactions. We leverage LangChain, LangSmith, and cutting-edge frameworks to optimize and automate prompt quality and conversation flows. We’re looking for a Prompt Engineer & AI Optimization Specialist who can implement and manage LangChain’s systematic approach to prompt optimization, creating self-improving systems to maximize AI performance.

Why This Role Matters

Voice AI is the Future: Our Voice AI system is central to how clients handle outbound prospecting, lead nurturing, and objection handling at scale.
LangChain-Driven Optimization: By leveraging LangChain’s prompt optimization workflow, you will implement structured processes to improve the effectiveness of prompts in a measurable way.
Systematic Optimization Techniques: You will apply state-of-the-art techniques such as meta-prompting, evolutionary optimization, and prompt gradients to enhance AI responses and outcomes.

What You’ll Do (Using LangChain’s Optimization Process)

Design and Implement Prompt Optimization Pipelines

Utilize LangChain’s workflow for prompt optimization, including methods such as Few-Shot Prompting, Meta-Prompting, and Prompt Gradients to drive iterative improvements.
Implement advanced techniques such as Meta-Prompting with Reflection, enabling LLMs to self-analyze and refine prompts.
Explore and apply Evolutionary Optimization to test variations in prompts and discover optimal configurations.

Automate Prompt Refinement with Feedback Loops

Set up automated feedback systems to monitor inference logs, user interactions, and downstream performance metrics.
Use tools like LangSmith to analyze and log prompt behavior, identifying areas for improvement and automating iterative updates.

Build Advanced Prompt Architectures

Create modular prompt structures for complex workflows, such as retrieval-augmented generation, dynamic memory, and context-aware flows.
Leverage chain-of-thought prompting and other advanced techniques to enhance the quality and accuracy of AI responses.

Implement Robust Evaluation Frameworks

Use LangChain’s evaluation tools to measure prompt effectiveness across qualitative and quantitative metrics.
Define benchmarks for success, such as latency, accuracy, coherence, and user satisfaction, to guide iterative improvements.

Collaborate Across Teams

Work with engineers to integrate prompt optimization workflows into production pipelines seamlessly.
Partner with product teams to ensure prompts align with evolving platform features and client needs.

Maintain and Scale Optimization Workflows

Document processes and maintain a version-controlled repository of prompt iterations.
Scale the optimization pipeline to handle increasing complexity as the platform grows.

What We’re Looking For

LangChain Expertise: Practical experience with LangChain’s frameworks for building and optimizing LLM-driven systems, including prompt evaluation and experimentation tools.
Prompt Engineering Mastery: Proven ability to design, test, and refine prompts for large language models (OpenAI, Anthropic, etc.) using structured processes.
Optimization Techniques: Familiarity with systematic methods such as Few-Shot Prompting, Meta-Prompting, Meta-Prompting with Reflection, and Prompt Gradients.
Feedback Loop Implementation: Experience setting up automated systems to evaluate and optimize prompts based on real-time data.
Technical Proficiency: Strong skills in Python, Git, and building scalable, production-ready workflows.
Data-Driven Mindset: Ability to analyze performance metrics and make informed decisions to improve AI outputs.
Collaborative Approach: Excellent communication skills and the ability to work across technical and product teams to align optimization efforts.

Why Join Us

High Impact: Your work will directly improve the performance of our AI platform, delivering measurable results for our clients.
Innovative Stack: We embrace cutting-edge tools like LangChain, LangSmith, and vector databases to push the boundaries of AI optimization.
Structured Innovation: You’ll work with proven methodologies like LangChain’s systematic prompt optimization, giving you a robust framework for success.
Collaborative Culture: We provide a supportive environment for experimentation, iteration, and growth.
Room to Grow: As we scale, you’ll have opportunities to expand the optimization framework, introduce new methodologies, and shape the future of our AI capabilities.

Interested?

Let’s connect! Please share your GitHub or relevant code samples, any prompts you’ve crafted, or stories about how you’ve implemented optimization workflows using LangChain. We’re excited to see how you approach prompt engineering and deliver real-world impact through systematic iteration.

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