Principal Engineer

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.

We are seeking a Cloud Generative AI and RAG Engineer with 2–3 years of professional experience to build, scale, and optimize GenAI applications.   He/She   will focus on building robust Retrieval-Augmented Generation (RAG) pipelines, writing clean Python production code, and deploying these solutions onto secure cloud infrastructure. Location : Bangalore(Onsite) Experience - 5 - 6+ Years 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.

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.

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.