AI Engineer

Full Job Description

We are looking for a talented AI Engineer to design, build, and maintain AI-powered consumer applications that help people understand, learn, communicate, and work more effectively. In this role, you will develop practical software products that solve real-world problems through artificial intelligence, automation, and intuitive user experiences.

Our first product, CAPCUE, demonstrates our vision of creating software that enhances human productivity and accessibility through AI. CAPCUE is a Windows desktop application that provides real-time AI-powered captions for any audio played on a computer, including meetings, lectures, livestreams, videos, podcasts, and other media sources.

As the company grows, we plan to develop additional consumer-focused software products across productivity, education, communication, accessibility, and other technology-driven categories. This role is ideal for an engineer who can combine strong software engineering skills with modern AI, LLM, and cloud-native development practices.

Responsibilities

• Design, develop, and maintain AI-powered consumer applications using modern engineering practices and scalable architectures.
• Build and integrate LLM-based features using models such as GPT, Claude, Gemini, and open-source LLMs.
• Develop and optimize RAG systems, including document ingestion, embeddings, vector search, retrieval pipelines, prompt engineering, and response generation.
• Build AI workflows involving speech-to-text, real-time transcription, natural language processing, summarization, classification, and automation.
• Design scalable backend services using Python, TypeScript, Node.js, PostgreSQL, Redis, Docker, and cloud services.
• Develop reliable APIs and services that support real-time AI functionality with low latency and high availability.
• Work with vector databases and search technologies such as Pinecone, Weaviate, Chroma, FAISS, pgvector, Elasticsearch, or similar tools.
• Improve AI system quality through prompt evaluation, automated testing, model monitoring, feedback loops, and performance optimization.
• Build observability into AI systems using logging, metrics, tracing, error tracking, and production monitoring tools.
• Collaborate with product, design, and engineering teams to translate product requirements into reliable AI-powered features.
• Participate in code reviews, architecture discussions, and technical planning to ensure code quality, scalability, security, and maintainability.
• Take ownership of features from design and development through deployment, monitoring, and continuous improvement.
• Contribute to the evolution of the company’s AI architecture, infrastructure, and development standards.

What You’ll Bring

• 4+ years of professional software engineering experience, with strong experience building production applications or backend services.
• Hands-on experience building AI-powered applications using LLMs, RAG, embeddings, vector databases, prompt engineering, and AI APIs.
• Strong programming skills in Python and/or TypeScript/Node.js.
• Experience working with LLM providers and frameworks such as OpenAI, Anthropic, Google Gemini, LangChain, LlamaIndex, Hugging Face, or similar tools.
• Strong understanding of AI application development, including prompt design, retrieval quality, model evaluation, latency optimization, and cost management.
• Experience with databases such as PostgreSQL, Redis, and vector search systems.
• Experience designing and consuming REST APIs, streaming APIs, and event-driven services.
• Familiarity with speech recognition, audio processing, transcription systems, or real-time AI pipelines is a strong plus.
• Experience with Docker and cloud platforms such as GCP, AWS, or Azure.
• Understanding of software engineering best practices, including clean code, testing, code reviews, CI/CD, version control, and production operations.
• Ability to debug complex systems, improve performance, and build reliable software for real users.
• Strong communication skills and the ability to work effectively in a collaborative product-focused environment.
• Experience with Agile software development practices.

Preferred Qualifications

• Experience building real-time AI applications, transcription tools, captioning systems, accessibility tools, or productivity software.
• Experience with Whisper, Deepgram, AssemblyAI, Google Speech-to-Text, Azure Speech, or other speech-to-text technologies.
• Experience deploying AI systems in production with monitoring, evaluation, and feedback collection.
• Familiarity with Kubernetes, serverless platforms, hybrid cloud infrastructure, or distributed systems.
• Experience optimizing AI systems for latency, accuracy, scalability, and cost efficiency.
• Experience working with open-source LLMs, model hosting, inference APIs, or fine-tuning workflows.
• Experience building consumer-facing desktop, web, or cross-platform applications.
• Strong interest in building AI products that improve accessibility, learning, communication, and productivity.

About the Role

This is a hands-on engineering role focused on building real AI products used by consumers. You will work across backend engineering, AI system design, LLM integration, RAG pipelines, real-time processing, and production deployment. The ideal candidate is not only comfortable using AI tools and APIs, but also understands how to build reliable, scalable, and user-friendly AI-powered software.

We are looking for someone who enjoys solving practical problems, shipping product features, and improving AI systems based on real user needs.