Forward Deployed Engineer II

Role Overview

• Embed with strategic enterprise customers to rapidly diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site
• Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications
• Drive rapid prototyping and POCs that demonstrate tangible business value within days to weeks
• Serve as the primary technical owner across the full project lifecycle: scoping, architecture, build, deployment, and post-launch optimization
• Architect production-grade Enterprise AI applications on Partner Foundry Solutions or Rackspace Private Cloud and GPU infrastructure, integrating with enterprise systems (ERP, CRM, data warehouses, data lakes)
• Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases (Pinecone, Weaviate, AstraDB), and knowledge base frameworks
• Develop and fine-tune LLM/SLM solutions; implement RAG architectures (LlamaIndex, Haystack) and orchestrate multi-agent workflows (LangChain, LangGraph, CrewAI)
• Ship with full-stack and DevOps depth: Python, Node.js/Go , React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management
• Champion observability, monitoring, and telemetry to ensure trustworthy, auditable, and versioned AI agents in production
• Identify expansion opportunities by working with sales and customer success to uncover high-value use cases across new business domains
• Feed structured field insights back to Platform Engineering and Product on feature gaps, emerging needs, and usability improvements
• Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that scale future engagements
• Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies.

Requirements

• BS/MS/PhD in Computer Science, Data Science, Engineering, Mathematics, Physics, or related field
• 3+ years in software engineering, data engineering, or AI/ML delivery; in customer-facing or field roles
• Proven track record in building and deploying AI/ML applications in production at enterprise scale
• Deep full-stack proficiency: Python (required), Node.js/Go , React/Vue, SQL/NoSQL databases
• Hands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks
• Strong DevOps skills: Docker, Kubernetes, CI/CD, GPU infrastructure, cloud-native deployment patterns
• Experience integrating across heterogeneous enterprise systems
• ERP, data warehouses, data lakes, streaming architectures
• Ability to translate ambiguous customer needs into actionable engineering plans under tight timelines
• Excellent communication skills
• comfortable with C-suite presentations, technical workshops, and cross-functional collaboration
• Willingness to travel up to 25% for on-site customer engagements.

Tech Stack

• Cloud
• Docker
• ERP
• ETL
• JavaScript
• Kubernetes
• Node.js
• NoSQL
• Python
• React
• SQL
• Vue.js
• Go

Benefits

• Professional development opportunities
• Flexible working hours
• Health insurance
• Paid time off