AI Engineer - Forward-Deployed AI Engineer

Forward-Deployed AI Engineer

Location: Charlotte, NC

Work Model: Hybrid (3 days onsite)

Duration: 9 Month Contract

Start Date: ASAP

Visa: USC / GC / H4/L2 / H1B / E3 / J2

Overview

We are seeking a highly technical and business-oriented Forward-Deployed AI Engineer to help design, build, and deploy enterprise-grade AI solutions that drive measurable business outcomes across the organization.

This role sits at the intersection of AI engineering, enterprise platforms, and business problem-solving. The ideal candidate will operate as a hybrid of a software engineer, AI solutions architect, and technical consultant — partnering directly with business, product, and engineering stakeholders to rapidly prototype and productionize AI-powered workflows, copilots, automations, and agentic systems.

The environment is fast-paced and highly collaborative, requiring someone comfortable navigating ambiguous problem spaces while delivering scalable and secure enterprise solutions.

Key Responsibilities

• Partner with business, product, and engineering teams to identify and define AI-driven solutions
• Design and build AI workflows, copilots, automations, and agentic systems using LLM technologies
• Develop and deploy scalable AI applications in enterprise production environments
• Integrate AI solutions with enterprise platforms such as ServiceNow, Salesforce, and internal systems through APIs
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines and orchestration frameworks
• Lead architecture discussions around prompt engineering, orchestration, APIs, and data integration
• Rapidly prototype solutions and transition them into production-ready systems
• Collaborate across business, engineering, security, and governance teams
• Ensure AI implementations align with enterprise security, risk, and compliance standards
• Contribute reusable AI frameworks, engineering standards, and best practices
• Own the full solution lifecycle from concept and POC through deployment and optimization
  
  

Required Qualifications

• 7 years of software engineering experience building production-grade applications
• Strong hands-on Python development experience
• Experience building and deploying AI/ML applications in enterprise environments
• 2 years of hands-on experience with LLM-based solutions and AI workflows
• Strong experience with APIs, integrations, and distributed systems
• Experience designing scalable end-to-end enterprise solutions
• Ability to translate ambiguous business problems into technical solutions
• Strong communication and stakeholder management skills
  
  

Preferred Qualifications

• Experience with OpenAI, Anthropic, LangChain, or similar AI platforms/frameworks
• Experience building AI agents, copilots, and RAG-based applications
• Integration experience with ServiceNow, Salesforce, or enterprise workflow platforms
• Experience working within regulated environments such as financial services
• Exposure to enterprise governance, security, and risk frameworks
• Consulting or customer-facing engineering experience
• Product-oriented mindset with strong focus on user experience and business impact
  
  

Technical Environment

• Python
• LLMs / Generative AI
• OpenAI / Anthropic APIs
• LangChain / Agentic Frameworks
• RAG Architectures
• APIs & Enterprise Integrations
• Distributed Systems
• Prompt Engineering
• AI Automation Platforms
• Cloud & Enterprise Platforms
  
  

Ideal Candidate

The ideal candidate combines strong software engineering fundamentals with hands-on AI implementation experience and the ability to work directly with stakeholders to solve complex business problems. This person should be equally comfortable architecting enterprise solutions, writing production-grade code, and driving AI adoption across cross-functional teams.

Skills: ai/lm,python,llm