Vibe Coding Jobs in the United States

The Practice Customer Engineer, Applied AI will serve as a technical lead for conversational AI engagements with public sector customers, designing cloud-native, scalable Generative AI solutions, building proofs-of-concept, and partnering with sales to present solutions to technical and executive stakeholders.

Lead and scale AI/ML engineering teams to design, build, and operate enterprise-grade machine learning and generative AI platforms. Drive MLOps/LLMOps infrastructure, model lifecycle management, and cloud-native productionization to enable reliable experimentation, deployment, monitoring, and governance across UnitedHealth Group businesses.

Senior AI/ML Engineer to design, build, and productionize generative AI and LLM solutions for enterprise healthcare use cases. The role focuses on LLM fine-tuning, retrieval-augmented generation (RAG), agentic systems, and ensuring reliability, safety, and monitoring in production environments.

Lead design and delivery of production-grade GenAI agentic systems for front-office Sales & Trading in Markets, embedding autonomous, multi-step workflows and secure integrations. Partner with product, data science, and business stakeholders to build, evaluate, and operate scalable, compliant agentic infrastructure.

Principal Architect - Artificial Intelligence to define and scale Wellmark's next-generation AI capabilities across risk management, product, claims, and enterprise productivity. Lead rapid prototyping and production of RAG pipelines, vector search, LLM-powered experiences and AI agents while implementing observability, governance, security, and cloud architecture practices.

Serve as an on-site AI Hackathon Mentor in Atlanta (March 20–24) to provide hands-on technical guidance, debugging, and architectural support as student teams build AI-powered prototypes. Mentor teams on prompt engineering, agent design, model selection, rapid prototyping, and pitch refinement during an intensive, short-term engagement paid via a fixed-fee stipend.

Build and scale an AI-ready data architecture for in-vivo biology labs at Pfizer, designing software and data products to extract insights from internal and public datasets and enable testable hypotheses across the drug discovery value chain. Lead development of data platforms, pipelines, integration, analysis, and collaborator onboarding to support translational research.

Pfizer is hiring an AI Data Engineer to design and scale an AI-ready data architecture for biologics research, extracting insights from internal and external datasets to enable hypothesis generation across drug discovery. The role focuses on building data products, analysis pipelines, and integration solutions for large-molecule therapeutics while collaborating across scientific and engineering teams.

Work hands-on to build autonomous and semi-autonomous AI systems that accelerate scientific discovery by generating molecular designs, proposing hypotheses, and integrating experimental feedback. Collaborate with scientists and engineers to prototype agent-based discovery pipelines and translate scientific goals into executable AI workflows.

As an Applied AI Customer Engineer on Google Cloud, you will provide technical expertise in Conversational and Generative AI to design scalable cloud architectures, build proofs-of-concept, and partner with sales to drive customer adoption and production deployments.

Build and deploy AI-driven applications and autonomous agents to improve Customer Operations at Qualtrics by leveraging Python and modern LLM frameworks. Collaborate with cross-functional teams and use AI-assisted coding tools to design, integrate, and automate solutions that close the loop on model performance.

Lead a Product Development POD to architect and build scalable, event-driven marketing orchestration and real-time customer engagement systems, combining big data engineering and AI-assisted development. Drive architecture, development, and team leadership to deliver high-performance data pipelines and personalized marketing experiences at scale.

Lead the design and architecture of AI-driven, cloud-native solutions and define AI-enabled SDLC practices within an Agile delivery model. Drive GenAI/LLM platform integration, infrastructure-as-code, DevSecOps, and mentor engineering teams to balance iterative delivery with architectural integrity and enterprise standards.

Senior AI Platform Engineer to design and implement the generative AI layer of the NEMESIS analytics platform, enabling natural-language interaction, conversational interfaces, prompt orchestration, retrieval pipelines, and visualization-on-demand. Hands-on role embedding LLM/SLM capabilities into production systems and collaborating with product and backend teams to deliver scalable GenAI features for business users.

You will own analytics for Paxos-issued stablecoins and rewards initiatives, building core metrics, dashboards, and analyses to guide product, rewards, and regulatory work. The role combines advanced SQL, dashboarding, data modeling (Snowflake + dbt), and AI-powered tooling to deliver decision-ready outputs across Product, Engineering, Finance, and Account Management.

Build and productionize backend systems and agentic GenAI solutions using Python and microservices. Focus on RAG pipelines, embeddings and vector DB integrations, LLM fine-tuning, and multi-agent orchestration to deliver scalable, performant AI systems for payment technology use cases.

Lead AI strategy and solution architecture for government and enterprise clients, defining practical, scalable AI roadmaps and governance while delivering hands-on prototypes. Act as a trusted advisor who designs real AI systems, translates technical tradeoffs for executives, and coaches organizations to adopt and sustain AI capabilities.

Lead AI Engineer to own the technical direction and delivery of Hilbert's agentic AI stack, building production-grade systems that perform multi-step inference across enterprise data silos. Hands-on role combining coding, architecture, and engineering leadership to ship reliable, evaluated, and integrated agent workflows for enterprise customers.

Lead design, implementation, and operation of agentic AI systems that combine LLMs, tools, planning, memory, evaluation, and multi-agent communication. Build AI services primarily in Python and integrate them into an enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure) to deliver trustworthy, low-latency production experiences.

Lead the build-out of data infrastructure and intelligent systems to enable AI-first analytics across a multi-brand consumer portfolio. Partner with business leaders to design and implement end-to-end data solutions, semantic layers, and AI-facing interfaces that provide a single source of truth for humans and AI agents.