[Hiring] AI Engineer @Lucidya

Role Description

As an AI Engineer, you will design, develop, and deploy AI-driven solutions that solve real-world business challenges. You will work across the full AI lifecycle—from data preparation and model development to deployment, monitoring, and optimization—while collaborating closely with product managers, software engineers, and domain experts.

This role is ideal for engineers with hands-on experience in machine learning and Generative AI who are passionate about building production-ready AI systems and delivering measurable business impact.

AI Development & Deployment

• Design, develop, and optimize machine learning and deep learning models for production environments.
• Build AI-powered features and services that address customer and business needs.
• Own the end-to-end AI lifecycle, including data exploration, model development, evaluation, deployment, monitoring, and continuous improvement.
• Perform model evaluation, error analysis, and performance optimization to ensure reliability and accuracy.

Generative AI & LLM Applications

• Develop and enhance AI applications powered by Large Language Models (LLMs).
• Build Retrieval-Augmented Generation (RAG) systems, semantic search solutions, and AI assistants.
• Work with embeddings, vector databases, and modern AI orchestration frameworks.
• Evaluate and improve model outputs for quality, relevance, latency, and user experience.

Production Engineering

• Deploy and maintain AI services in cloud and containerized environments.
• Build scalable APIs and inference pipelines for real-time and batch processing workloads.
• Monitor AI systems in production and troubleshoot performance or reliability issues.
• Collaborate with engineering teams to integrate AI capabilities into customer-facing products.

Collaboration & Innovation

• Partner with Product, Engineering, Data, and Customer Success teams to translate business requirements into AI solutions.
• Contribute to technical discussions, design reviews, and AI best practices.
• Stay up to date with emerging AI technologies and recommend practical innovations that create business value.

Qualifications

• 2–4 years of professional experience in Artificial Intelligence, Machine Learning, Data Science, or related engineering roles.
• Proven experience developing and deploying AI or machine learning solutions into production environments.

Requirements

• Strong proficiency in Python.
• Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of machine learning fundamentals, model evaluation techniques, and performance optimization.
• Experience building AI applications using Large Language Models (LLMs).
• Familiarity with Retrieval-Augmented Generation (RAG), embeddings, and vector search concepts.
• Experience building APIs using FastAPI, Flask, or similar frameworks.
• Understanding of software engineering best practices, version control, and testing methodologies.
• Experience deploying AI models into production environments.
• Familiarity with Docker and cloud platforms such as AWS, Azure, or GCP.
• Understanding of monitoring, observability, and AI system reliability.
• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to work effectively in a fast-paced, cross-functional environment.

Preferred Qualifications

• Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
• Experience working with vector databases such as Pinecone, Qdrant, ChromaDB, Weaviate, or FAISS.
• Exposure to agent-based AI systems and workflow automation.
• Experience with MLOps practices, CI/CD pipelines, and model monitoring.
• Experience with computer vision, multimodal AI, recommendation systems, or NLP applications.
• Familiarity with self-hosted open-source models and modern inference frameworks.

What Success Looks Like

• Deliver production-grade AI solutions that create measurable business impact.
• Contribute to Lucidya's next generation of AI-powered products and capabilities.
• Improve model performance, reliability, and scalability across AI services.
• Collaborate effectively with engineering and product teams to bring AI innovations to market.
• Continuously expand Lucidya's AI capabilities through practical experimentation and execution.