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Lead AI Engineer

TPA technologies
4 hours ago
Full-time
On-site
W2 ONLY

Below covers everything you need to know about what this opportunity entails, as well as what is expected from applicants.

No C/C

No Corp-to-Corp employers

100% remote

Lead AI Engineer Location: Remote Duration: Contract Work Authorization: USC or GC only Interview Process: Background check required Important: Candidates must be able to travel to one of the client’s offices on Day 1 for onboarding verification: Denver, CO; New York, NY; Atlanta, GA; Plymouth Meeting, PA; Overland Park, KS; or St. Petersburg, FL.

We are seeking an experienced Lead AI Engineer to help turn AI initiatives into secure, production-ready, enterprise-scale solutions. This role will focus heavily on Agentic AI systems and will partner closely with AI, engineering, and product teams. The ideal candidate brings a strong blend of hands-on engineering expertise, architecture knowledge, and leadership ability. This person will help bridge business needs, technical standards, and implementation to ensure AI solutions are scalable, reproducible, secure, and aligned with long-term enterprise strategy. Key Responsibilities Design, build, and deploy full-stack applications using Python and React Architect secure, scalable systems with strong focus on security, compliance, and best practices Lead internal AI initiatives, including support of existing AI-enabled products and delivery of new AI-driven solutions Provide guidance to teams on how to leverage AI effectively across the organization Build and integrate agentic AI systems using modern LLM and GenAI technologies Collaborate with cross-functional teams to scope, prototype, and deliver AI solutions quickly Serve as a technical partner to business teams to identify AI opportunities that improve efficiency, reduce risk, and enhance customer experience Integrate GenAI models into full-stack applications and internal workflows Contribute to prompt engineering, fine-tuning, and evaluation of model outputs Build reusable services for multi-agent orchestration and task automation Optimize AI inference pipelines for scalability, latency, and cost efficiency Participate in architectural discussions and contribute to the technical roadmap Required Qualifications 7+ years of full-stack development experience with technologies such as Python, JavaScript, Node.js, and React Strong experience with LLM frameworks such as LangChain and Bedrock xsgimln Experience with AI-enabled workflows and data processing in Python Strong knowledge of LLMs, prompt engineering, RAG architecture, and Agentic AI Deep understanding of embeddings, vector databases, and retrieval pipelines Experience with Git, CI/CD, DevOps, and production-grade GenAI deployment practices Hands-on experience with Docker, Kubernetes, and cloud-native deployment Knowledge of AI observability, model monitoring, and cost optimization Strong communication skills with ability to work across technical and non-technical teams Experience working with distributed engineering teams Preferred Qualifications Experience in financial services or other highly regulated environments Familiarity with core banking systems or similarly complex enterprise platforms