AI Engineer at PlutusAI
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.
