Sr. AI Engineer

About Us

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.

Job Role : Senior AI Engineer

Experience – 2-5 Years

Full-Time · Bangalore · Hybrid

Education:

Bachelor's or Master's in CS, AI/ML, Data Science or equivalent

practical experience

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

CERTIFICATIONS  (PREFERRED)

Cloud AI certifications: AWS, Azure, or GCP

RPA platform certifications: UiPath or Automation Anywhere

SCOPE & GROWTH PATH

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

RESPONSIBILITIES

SKILLS:

AGENTIC AI

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 

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 AutomateBot workflows with exception handling, logging & integration with agent layersENGINEERING

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)

 Responsibilities

AGENT DEVELOPMENT & IMPLEMENTATION

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 

RAG & KNOWLEDGE SYSTEMS

Build end-to-end RAG pipelines: ingestion, chunking, embedding, vector store & retrieval evaluationMonitor and improve retrieval quality; integrate RAG as knowledgebackend for agents

RPA & HYBRID AUTOMATION

Develop and maintain RPA task bots; implement AI agent ↔ RPA handoff logicPRODUCTION & QUALITY

Write unit & integration tests; contribute to CI/CD pipelines & prompt versioningMonitor deployed systems; participate in incident response for agent failure modes 

COLLABORATION & GROWTH

Work closely with Senior Engineers, taking increasing ownership of components over timeParticipate in stakeholder use-case discovery; document pipelines & agent configurations clearly