Principal Engineer

About Us

Key Responsibilities

• GenAI & RAG Development: Design, implement, and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines to improve LLM accuracy.
• Python Engineering: Write clean, modular, and highly efficient backend code using Python frameworks like FastAPI or LangChain.
• Cloud Architecture: Deploy, secure, and scale GenAI applications on cloud platforms (AWS, GCP, or Azure).
• Vector Database Management: Manage and tune Vector Databases to ensure fast, relevant semantic search retrieval.
• API Integration: Connect application frontends and internal data systems with enterprise LLMs via secure APIs.
• System Monitoring: Track LLM token usage, response latency, and retrieval accuracy in production.
• Required Skills & Qualifications
• Experience: 5–6+ years of cloud engineering experience and AI solution development.
• Python Mastery: Expert-level Python skills, with a focus on asynchronous programming and API development.
• GenAI Ecosystems: Hands-on experience using frameworks like LangChain, LlamaIndex, Hugging Face or any similar framework.
• Vector Databases: Practical experience with databases such as Vespa, Pinecone, Milvus, Chroma, or any similar database.
• Cloud Infrastructure: Proven experience in deploying band managing cloud compute (Docker, Kubernetes) and serverless services.
• Prompt Engineering: Ability to systematically design and optimize prompts for specific business use cases.

Preferred Qualifications

• Familiarity with fine-tuning open-source LLMs (e.g., Llama, Mistral).
• Experience setting up MLOps/LLMOps tracking tools (e.g., LangSmith, Weights & Biases).
• Cloud certifications focusing on DevOps or Developer pathways.
• Education
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
• All unsolicited resumes submitted to any @automationanywhere.com email address, whether submitted by an individual or by an agency, will not be eligible for an agency fee.

Qualifications

• 5 - 6+ Years
• 5–6+ years of cloud engineering experience and AI solution development.
• Python Mastery: Expert-level Python skills, with a focus on asynchronous programming and API development.
• GenAI Ecosystems: Hands-on experience using frameworks like LangChain, LlamaIndex, Hugging Face or any similar framework.
• Vector Databases: Practical experience with databases such as Vespa, Pinecone, Milvus, Chroma, or any similar database.
• Cloud Infrastructure: Proven experience in deploying band managing cloud compute (Docker, Kubernetes) and serverless services.
• Prompt Engineering: Ability to systematically design and optimize prompts for specific business use cases.