Sr. AI Engineer
Automation Anywhere
Senior 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.
Experience – 2-5 Years
Full-Time · Bangalore · Hybrid
Education:
Bachelor's or Master's in CS, AI/ML, Data Science or equivalent
practical experience
2-5 years in software engineering; 2+ years building AI-powered or automation solutions in production
Evidence of delivering complete, working solutions — not just experimental or prototype work
Cloud AI certifications: AWS, Azure, or GCP
RPA platform certifications: UiPath or Automation Anywhere
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
Hands-on with LangChain/LangGraph, AutoGen, or CrewAICore agent patterns: tool use, memory, multi-step reasoning, output validationLLM APIs (OpenAI, Anthropic, Gemini, or open-source); structured prompt engineering
End-to-end RAG pipelines: ingestion, chunking, embedding, retrieval evaluation
Familiarity with at least one vector database; ability to diagnose & improve retrieval quality
Hands-on with UiPath, Automation Anywhere, or Power AutomateBot workflows with exception handling, logging & integration with agent layers
Strong Python; cloud AI services; APIs, data pipelines & event-driven systems
Exposure to LoRA/QLoRA fine-tuning (growth area); agent observability tooling (LangSmith, Arize)
Build and maintain multi-agent workflows from Solution designs document into production-ready implementationsImplement tool integrations (APIs, ERP, CRM, ITSM) with error handling & graceful degradation
Build end-to-end RAG pipelines: ingestion, chunking, embedding, vector store & retrieval evaluationMonitor and improve retrieval quality; integrate RAG as knowledge backend for agents
Develop and maintain RPA task bots; implement AI agent ↔ RPA handoff logic
Write unit & integration tests; contribute to CI/CD pipelines & prompt versioningMonitor deployed systems; participate in incident response for agent failure modes
Work closely with Senior Engineers, taking increasing ownership of components over timeParticipate in stakeholder use-case discovery; document pipelines & agent configurations clearly