AI Engineer
Automation Anywhere
AI 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.
Implements designs under Senior Engineer guidance
Grows toward independent architecture ownership
Develops fine-tuning expertise as a growth area in role
Progresses toward leading stakeholder discovery independently
Experience: 1-2 years
Skills:
Agentic AI
Hands-on with LangChain/LangGraph, AutoGen, or CrewAICore agent patterns: tool use, memory, multi-step reasoning, output validation
LLM APIs (OpenAI, Anthropic, Gemini, or open-source); structured prompt engineering
RAG & Vector Infrastructure
End-to-end RAG pipelines: ingestion, chunking, embedding, retrieval evaluation
Familiarity with at least one vector database; ability to diagnose & improve retrieval quality
RPA
Hands-on with UiPath, Automation Anywhere, or Power Automate Bot workflows with exception handling, logging & integration with agent layers
Engineering
Strong Python; cloud AI services; APIs, data pipelines & event-driven systems
Nice to have:
Exposure to LoRA/QLoRA fine-tuning (growth area); agent observability tooling (LangSmith, Arize)
Education:
Agent Development & Implementation
Build and maintain multi-agent workflows from Solution designs document into production-ready implementations
Implement tool integrations (APIs, ERP, CRM, ITSM) with error handling & graceful degradation
RAG & Knowledge Systems
Build end-to-end RAG pipelines: ingestion, chunking, embedding, vector store & retrieval evaluation
Monitor and improve retrieval quality; integrate RAG as knowledge backend for agents
RPA & Hybrid Automation
Develop and maintain RPA task bots; implement AI agent ↔ RPA handoff logic
Production & Quality
Write unit & integration tests; contribute to CI/CD pipelines & prompt versioning
Monitor deployed systems; participate in incident response for agent failure modes
Collaboration & Growth
Work closely with Senior Engineers, taking increasing ownership of components over time
Participate in stakeholder use-case discovery; document pipelines & agent configurations clearly