Collabera Wells Fargo - AI Engineer (Forward-Deployed AI Engineer)

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.