AI Engineer - Forward-Deployed AI Engineer
Client: Wells Fargo
Hiring Manager: Rachit Mathur
Location: Charlotte, NC
Work Model: Hybrid (3 days onsite)
Duration: 9+ Month Contract
Start Date: ASAP
Line of Business: COO
Visa: / /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 is someone who 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.
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