Forward Deployment 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 industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall 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.

QUALIFICATIONS

Education: Bachelors or Masters in CS AI/ML Data Science or equivalent practical experience

Experience: 58 years in software engineering; 3 years building production-grade automation solutions

Demonstrated end-to-end delivery of agentic AI systems or complex enterprise RPA prototypes

Certifications (Preferred): AWS Azure or GCP; RPA platforms such as UiPath or Automation Anywhere

Scope: Leads solution architecture independently owns LLM adaptation strategy end-to-end mentors junior engineers; leads stakeholder discovery workshops

SKILLS

Agentic AI: LangChain/LangGraph AutoGen CrewAI

Agent patterns: tool use memory multi-agent coordination guardrails failure recovery

LLM Fine-Tuning & Adaptation: LoRA/QLoRA with HuggingFace PEFT or Unsloth; Dataset prep evaluation benchmarking model versioning; Serving fine-tuned models:vLLMGPTQ GGUF

RAG & Vector Infrastructure: Pinecone Weaviate Qdrant; embeddings retrieval evaluation

RPA: UiPath Automation Anywhere Power Automate in production

Engineering: Python (production quality); Cloud AI services (BedrockAzure OpenAI Vertex AI)

RESPONSIBILITIES

Agent Design & Engineering:

• Architect multi-agent systems with branching logic exception handling & human-in-the-loop escalation.

• Define agent tool integrations memory context management & state persistence.

LLM Adaptation Strategy:

• Own fine-tuning strategy (fine-tune vs RAG vs prompt engineering) and deliver end-to-end

• Manage GPU training runs model merging quantization & production serving

RPA & HYBRID AUTOMATION:

• Build RPA task bots as execution layers within agentic workflows

• Architect AI agent RPA handoff logic and exception management

Production & Operations:

• Build agent evaluation frameworks; implement observability & tracing (LangSmith Arize)

• CI/CD for agent/model deployments; diagnose hallucination tool misuse & cost runaway

Stakeholder & Leadership:

• Lead use-case discovery workshops; communicate architecture trade-offs to non-technical audiences