AI Engineer — Clarity Coach

AI Engineer — Clarity Coach Location: Remote Type: Contract or Part-Time to Full-Time Reports to: Founder / Product Lead Product: Career Compass, an AI-powered career clarity platform helping professionals assess their resume, LinkedIn profile, job fit, stability risk, and career next steps. About Career Compass Career Compass is building an AI-powered platform for professionals who need practical, personalized career guidance. The product helps users understand where they stand, improve their career materials, evaluate job opportunities, and receive clear action plans. Our MVP includes features such as: • Resume Analyzer • Job Description Analyzer • LinkedIn Optimizer • Career Stability Assessment • Personalized Career Action Plan • Future interview and coaching features We are looking for an AI Engineer who can turn product ideas, prompts, and business requirements into reliable AI-powered features that users can actually trust and use. Role Overview We are hiring an AI Engineer to build, test, and improve the AI systems behind Career Compass. This person will work closely with the founder, product/business team, and UI/UX or full-stack developers to turn feature requirements into functional AI workflows. This is not just a “prompt writing” role. We need someone who can build structured AI pipelines, improve output quality, connect AI logic to the product, and help create a scalable foundation for future career coaching capabilities. Key Responsibilities AI Feature Development • Build AI-powered workflows for resume analysis, LinkedIn optimization, job description matching, career recommendations, and action planning. • Translate business logic and product requirements into AI prompts, scoring logic, structured outputs, and backend workflows. • Develop reusable prompt templates and AI chains that can support multiple user journeys. • Ensure AI outputs are structured, useful, consistent, and aligned with the product experience. Prompt Engineering & Evaluation • Design and refine prompts for different Career Compass features. • Create prompt variants and test them across different user profiles, resumes, industries, and career stages. • Build simple evaluation methods to measure output quality, accuracy, relevance, tone, and usefulness. • Identify where the AI is vague, generic, inconsistent, or misaligned with the intended coaching experience. AI Architecture & Integration • Recommend the right AI architecture for MVP and post-MVP features. • Work with developers to integrate AI workflows into the app. • Structure inputs and outputs so the AI can return reliable JSON or formatted responses for the frontend. • Support API integration with LLM providers such as OpenAI, Anthropic, or similar platforms. • Help define what should happen in the backend versus the frontend. Product Quality & Reliability • Improve AI response quality so users receive clear, personalized, practical career guidance. • Reduce hallucinations, generic advice, and inconsistent scoring. • Build guardrails for sensitive career advice, user data handling, and professional tone. • Support testing across sample resumes, LinkedIn profiles, job descriptions, and career scenarios. Documentation • Document prompts, AI workflows, assumptions, scoring logic, and feature behavior. • Create technical notes that explain how each AI feature works. • Help maintain a clear AI feature specification that engineers, product, and QA can understand. Required Experience • Experience building AI-powered applications using LLMs. • Strong prompt engineering experience beyond basic chatbot prompts. • Ability to structure AI outputs using JSON, schemas, or defined response formats. • Experience with APIs and backend integration. • Familiarity with OpenAI, Anthropic, LangChain, LlamaIndex, or similar AI development tools. • Ability to test AI outputs and improve quality through iteration. • Strong problem-solving skills and ability to work from imperfect product requirements. • Clear documentation skills. Preferred Experience • Experience building career, HR tech, coaching, education, recruiting, or resume-related products. • Experience with RAG, embeddings, vector databases, or document parsing. • Experience with resume parsing, PDF extraction, or profile analysis. • Familiarity with evaluation frameworks for LLM applications. • Experience working with startup MVPs. • Understanding of responsible AI, privacy, fairness, and bias considerations. Technical Skills The ideal candidate should be comfortable with some or most of the following: • Python or JavaScript/TypeScript • LLM APIs • Prompt engineering • JSON schema design • API integration • Backend workflows • LangChain, LlamaIndex, or similar frameworks • Vector databases or embedding workflows • GitHub • Basic cloud deployment concepts • No-code/low-code AI tools as needed What Success Looks Like Within the first 30–60 days, this person should be able to: • Understand the Career Compass product vision and MVP features. • Review the existing product requirements and identify AI implementation gaps. • Build or improve the AI logic for at least 2–3 core features. • Create structured prompt templates and output formats. • Help the development team understand exactly how the AI should work. • Improve the quality, consistency, and usefulness of AI-generated recommendations. • Produce clear documentation for the AI workflows. Example Projects The AI Engineer may work on projects such as: • Creating a resume scoring and feedback engine. • Building a JD-to-resume match analysis workflow. • Generating personalized LinkedIn headline, About section, and experience recommendations. • Creating a career stability risk assessment based on user inputs. • Generating a personalized 30-day career action plan. • Designing AI output templates that can be displayed cleanly in the app. • Building test cases for different personas, such as recent graduates, mid-career professionals, executives, career switchers, and immigrants entering a new market. Data: It’s in unstructured formats: pdf,csv, json Who You Are You are a builder who can take a messy product idea and turn it into a working AI feature. You understand that good AI products require more than calling an API. You care about user experience, output quality, testing, structure, and reliability. You are comfortable working in an early-stage environment where requirements evolve quickly, but you can still create order, documentation, and production-ready logic. Nice-to-Have Mindset We are especially interested in someone who: • Thinks like a product engineer, not just a model user. • Can challenge unclear requirements respectfully. • Understands that career advice must be practical, specific, and responsible. • Can balance speed with quality. • Can help us avoid generic AI outputs that feel like every other career tool. Compensation Compensation will be based on experience, availability, and engagement structure. We are open to contract, part-time, or fractional support to start, with potential to expand as the product grows. How to Apply Please send: • Your resume or LinkedIn profile • Examples of AI products, workflows, or prototypes you have built • A brief note describing your experience with LLMs, prompt engineering, and AI application development • Any relevant GitHub, portfolio, or product demos