AI Engineer

• AI Implementation - Design, build, and maintain all of our AI systems across the company. Everything from internal marketing, sales, finance, and operations systems to local AI systems in our engineering workflows, and the Chamber itself.
• AI Adoption - Educate, Train, Support, and Uplift everyone in the company with their AI adoption. Running office hours, making tutorials, providing resources, sourcing solutions, and more.
• AI Infrastructure - Architect and operate a scalable set of infrastructure that allows non-technical, and technical teams to use AI in a secure and productive manner.
• AI Systems & Agents - In conjunction with departments, design, build and maintain all AI systems and agents. This includes administering and managing our off the shelf AI systems like Claude, Viktor, Cursor, etc. It also includes our custom built Agents, Skills, Plugins, Tools, and more.
• AI Security - You are responsible for creating, maintaining, and enforcing all data, privacy, and security policies across our AI systems and Agents. Organization, Department, and Role based permissions and settings across all our products.
• Other Projects - As this is a technical role, you will also be asked to help build other internal systems like automations, micro apps, and more.

AI Solutions Lead

• Leading cloud VM platform initiatives from architecture and systems design through implementation, testing, and deployment.
• Designing, building, and operating scalable services that support secure, isolated agent workloads.
• Developing automation for infrastructure provisioning, VM lifecycle management, application delivery, configuration, monitoring, and remediation.
• Collaborating with engineering teams across NVIDIA to translate business and AI workflow requirements into dependable platform capabilities.
• Improving the platform’s reliability, scalability, observability, performance, and operational efficiency.
• Continuously raising standards for code quality, testing, documentation, infrastructure security, and production readiness.

Senior Software Engineer, AI Agent Compute

• Lead and mentor teams of data scientists and ML engineers
• Manage client relationships and promote satisfaction with deliverables
• Translate intricate business challenges into AI-driven strategies
• Design and implement AI solution architectures
• Drive innovation and excellence in client engagements
• Analyze data to derive actionable insights and solutions
• Collaborate with stakeholders to align on project objectives
• Uphold exceptional standards of quality and integrity in every task

ERP AI Engineer – Manager

• Analyzing client needs to implement and integrate business applications effectively
• Providing training and support to clients for seamless utilization of software solutions
• Leveraging analytical reasoning to optimize operational efficiency through business applications
• Collaborating with clients to understand and address their strategic objectives
• Utilizing business data analytics to inform insights and recommendations
• Managing project delivery and resource management to meet client expectations
• Implementing technology solutions to support business transformation initiatives
• Developing documentation to support application software implementation and integration
• Engaging in strategic planning to align technology solutions with business goals
• Navigating complex situations to build meaningful client relationships and inspire team members

AI Integration Developer, Senior Associate

• Act as a trusted advisor to leadership, guiding the development and influence of applications, networks, information security, databases, operating systems, web technologies, and emerging AI capabilities to address highly complex business and technical needs across multiple groups
• Lead the strategy and resolution of highly complex, unique challenges through end‑to‑end solution design, including Generative and Agentic AI systems, cloud‑native platforms, and legacy modernization efforts that require long‑term vision, creativity, innovation, and advanced analytical thinking
• Translate advanced technology expertise, deep understanding of enterprise business objectives, organizational structure, and the broader technology ecosystem into scalable engineering solutions, such as reusable architectures, AI-enabled platforms, and production‑ready systems
• Provide vision, direction, and technical leadership to senior leaders on implementing innovative business solutions, embedding AI and automation into product delivery workflows, decision support, and developer productivity while ensuring alignment with security, compliance, and responsible AI standards
• Maintain deep awareness of industry best practices, emerging technologies, and AI advancements, proactively recommending innovations that modernize operations, improve efficiency and quality, and create competitive advantage for the organization
• Strategically engage with professionals and managers at all levels of the enterprise, serving as an expert technical advisor and escalation point for complex platform, data, and AI decisions while mobilizing and guiding large‑scale, cross‑organizational initiatives and communicating progress to executive leadership

Principal AI Engineer

• Writes, tests and refines prompts across Tax, Assurance, Advisory and Wealth Management use cases, following the architectural standards and prompt patterns established by the Workflow Architect.
• Builds, maintains and versions Claude skills and workflow components, managing the full lifecycle from development through testing to production deployment.
• Curates and organizes the Firm’s prompt library, tagging entries by service line, use case type, complexity tier and validation status to maximize discoverability and reuse across teams.
• Conducts quality assurance testing on AI outputs, including accuracy validation, edge case testing, hallucination detection and compliance checks against the Firm’s professional standards.
• Supports the Ambassador network by providing hands-on technical assistance, troubleshooting workflow issues and delivering implementation guidance when new tools and skills launch.
• Documents prompt engineering patterns, skill specifications and build processes in the CoE knowledge base, creating the reference material that enables the team to scale.
• Collaborates with service line professionals and subject matter advisors to capture domain-specific requirements and translate them into prompts and skills that reflect how work actually gets done.
• Participates in use case intake, evaluating submitted ideas from across the Firm for technical feasibility, effort estimate and alignment with the existing production roadmap.
• Monitors AI platform updates and new capabilities (e.g., Anthropic Claude releases, new tool-use and agentic features) and assesses their impact on existing skills and workflows.
• Contributes to the Firm’s AI training materials by developing prompt examples, live skill demonstrations and technical reference guides that the Coordination Track uses for Ambassador enablement.

AI Prompt Engineer

• Design, develop, and improve scalable infrastructure to support the next generation of AI applications
• Drive improvements in architecture, performance, and reliability
• Collaborate across hardware, software, and research teams
• Stay informed of the latest advancements in AI infrastructure

Senior Applied AI Engineer

• Deliver agentic AI solutions in production.
• Design, build, and ship AI agents for a partner business domain using the team’s internal platform and reusable components — owning the solution from first workshop to production operation.
• Partner deeply with the business. Embed with business organizations to understand their workflows, data, and operational touchpoints; identify where agentic AI delivers measurable improvement; and translate domain knowledge into technical designs.
• Build quickly and iterate. Compose solutions from platform capabilities rather than rebuilding from scratch; prototype fast, validate with users, then harden for production. Speed with rigor is the job.
• Apply state-of-the-art techniques. Use foundation models, LLM orchestration, retrieval, and transformer-based approaches for sequential and transactional data — choosing the simplest technique that ships.
• Own production quality. Build the evaluation, observability, and guardrail systems for everything you ship; ensure deployed agents meet the bank’s reliability, security, and compliance standards.
• Strengthen the platform. Contribute improvements, patterns, and reusable components back to the platform team so every delivery makes the next one faster.
• Communicate outcomes. Translate technical progress into presentable results — supporting partner stakeholder reviews and executive demos with clarity and credibility.

Lead Applied AI Engineer

• Architect and implement artificial intelligence and machine learning systems addressing diverse business challenges throughout the Bank
• Conduct rigorous data analysis and perform statistical evaluation
• Design experimental frameworks and develop algorithms leveraging both structured and unstructured data
• Create on-demand analytics to fully integrated software systems
• Stay apprised of and educate leaders on emerging AI trends, risks, and opportunities
• Create and maintain model documentation for transparency
• Research, test, and apply state-of-the-art generative AI models and/or solutions
• Develop agentic AI systems capable of autonomous reasoning, planning, and tool utilization
• Create evaluation frameworks to assess model performance
• Translate business questions into analytical problems with clear objectives
• Lead projects with limited supervision, influencing technical direction and standards
• Partner with cross-functional teams to understand business requirements and translate into technical solutions

Principal AI Engineer – AI Transformation

• Use AI for solving product problems in gaming and other interactive experiences.
• Build upon the latest research to create new models and invent new ways of applying AI to advance neural graphics and gaming.
• Create prototypes to demonstrate real-life applications of your ideas and to accelerate productization.
• Keep up with the latest AI/DL research and collaborate with diverse teams (both internal and external to NVIDIA), including AI/DL researchers, hardware architects, and software engineers.
• Participate in technology transfers to and from teams across NVIDIA.

Senior Machine Learning Graphics Engineer, AI for Experiences

• Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
• Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
• Build and operate LLM evaluation and batch-analysis pipelines
• Own traditional ML workflows from data to scheduled production inference
• Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Senior Software Engineer – Applied AI

• Lead the product strategy, roadmap, and delivery of AI-enabled solutions, translating complex business challenges into scalable products that drive measurable operational and customer outcomes.
• Define and optimize human-AI interaction models, including conversational experiences, prompt strategies, decision-support tools, and human-in-the-loop workflows that improve adoption, trust, and productivity.
• Partner closely with Engineering, Data Science, Operations, and Risk/Governance teams to prioritize opportunities, define requirements, and deliver AI products from concept through deployment and continuous optimization.
• Own product discovery and solution design by translating business needs into AI use cases, product requirements, user stories, success metrics, and implementation plans aligned to enterprise objectives.
• Balance innovation with governance by ensuring AI solutions adhere to enterprise controls, regulatory requirements, risk frameworks, and responsible AI principles within a highly regulated environment.
• Establish scalable product frameworks, reusable AI patterns, and best practices that accelerate AI transformation initiatives, modernize workflows, and unlock sustainable business value across the organization.
• Partner with oversight and governance contacts within ECRL as well as enterprise teams such as the COO Gen AI COE and Model Risk Management (MRM) on design validation, AI use case development, and model ownership.
• Serve as the user experience design lead on AI solutions, leaning on design thinking to establish fit for purpose delivery of technology solutions tied directly to operational goals.
• Partner with the product delivery team to ensure intent of design is maintained through delivery, testing is completed, and software development lifecycle (SDLC) and model development lifecycle (MDLC) requirements are met.
• Develop an integrated view of customer experiences across the Enterprise, ensuring interdependencies across organizations and functions are understood and map business capabilities to the business systems managed by IT to identify and resolve inconsistencies, duplications or gaps.
• Acts as a liaison between client area and technical organization by planning, conducting, and directing the analysis of current state and future state design.
• Conduct people, process, data, logic/ calculation and systems deep dive current state assessments to ensure all redundancies, deficiencies, failure points and constraints are understood and addressed.
• Recommend solutions from a people, process, business intelligence and technology perspective to standardize, streamline, and install appropriate control mechanisms for enhanced business performance, customer excellence, productivity, improved quality, etc.
• Conduct change impact analysis and develop capability gap closure roadmaps including short- and long-term implementation recommendations.
• Ensure target state alignment between the business model, operating model, organizational structure and IT solutions and capabilities.
• Consults with Enterprise Architects to ensure integration across domains.
• Identify risk through these transformations and evaluate and install appropriate control mechanisms to minimize risk.
• Perceives the impact and implications of decisions on other components of the company as well as impact on investors, customers and clients.
• Be an active voice to recommend solutions that will exploit opportunities and address critical deficiencies. Will also work closely with business lines and leadership across Wells Fargo in the execution of this strategy.

Senior Lead AI Transformation, Product Strategy

• This role is a Senior Product Owner in the Scaled Agile Framework who partners with product managers to balance business, technology and design priorities to deliver brand-defining product and service experiences.
• The Senior Product Owner is responsible for executing the strategy for their area of responsibility based on client and company needs, which can include client experience, back office processes or systemic processes outside the client journey.
• They are a key resource in backlog management for the teams.
• The Product Owner works hand-in-hand with Product Managers to translate the product vision into epics and features that can be actioned by the delivery teams.
• The work will span the entire delivery process; from assisting with identification of areas for improvement, to more detailed work in authoring user stories, working closely with technical leads/scrum teams to ensure the solution effectively addresses experience priorities while maintaining technical integrity, and overseeing tactical execution of efforts.
• The Senior Product Owner is expected to be a thought leader in delivering complex technology projects to market.

Senior Product Manager – Wholesale Lending, Sales Enablement AI Platform

• Design, develop, test, deploy, and maintain AI-enabled software applications, machine learning services, APIs, and enterprise software solutions.
• Develop software that leverages artificial intelligence, machine learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other modern AI capabilities to improve business processes and user experiences.
• Collaborate with Product Management, Data Science, Engineering, and business stakeholders to translate functional requirements into scalable technical solutions.
• Implement high-quality, maintainable, and secure software following established software engineering, AI development, and coding standards.
• Contribute to AI model integration, prompt engineering, model evaluation, testing, monitoring, and deployment activities.
• Participate in software architecture discussions, design reviews, code reviews, and technical planning sessions.
• Troubleshoot, analyze, and resolve moderately complex software, AI, integration, and platform issues.
• Develop automated tests, CI/CD pipelines, and deployment processes to improve software quality and delivery efficiency.
• Evaluate new AI frameworks, libraries, cloud services, and engineering tools to improve development productivity and product capabilities.
• Contribute to technical documentation, design specifications, user training, knowledge sharing, and engineering best practices.
• Partner with Quality, Regulatory, Security, Privacy, and Compliance teams to support secure, reliable, and compliant software development.
• Support production operations, incident response, defect resolution, and continuous improvement initiatives.
• Participate in cross-functional AI and software engineering initiatives.
• Learn and adopt emerging AI technologies, software frameworks, and engineering practices.
• Support enterprise modernization and automation initiatives.
• Contribute to special projects or temporary assignments as needed.

Forward Deployed Engineer – Software Development Engineer – Artificial Intelligence, AI

• Own stakeholder relationships across Medbridge’s executive team, working with them to find the problems and AI enabled solutions that can expedite, or remove, the current blockers in the business.
• Design, build, and ship AI-powered features across our internal teams, from the user interface to the backend services and AI workflows behind it.
• Build full-stack applications using AI-native engineering workflows and tools such as Claude, Cursor, Codex, and OpenAI and Anthropic APIs.
• Develop APIs, backend services, and automation pipelines that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, DevOps, and MLOps best practices to the testing, deployment, monitoring, evaluation, and optimization of AI solutions.
• Partner closely with our Product and Engineering teams to turn ambiguous goals into scalable internal products.
• Use AI tooling throughout your workflow (coding, code review, testing, and planning) and help push the team’s adoption forward.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks, and bring what works back to the team.
• Instrument what you ship and use usage data and evidence to decide what to build, fix, or kill next.

Product Engineer – AI

• design, develop, and deliver high-quality, secure, and user-centric software solutions
• collaborate cross-functionally to build scalable applications
• lead projects and mentor peers
• develop software focused on simplification, UX, security, and user privacy
• build advanced agentic AI applications that automate complex business processes
• proven expertise in designing and deploying enterprise-grade AI systems
• full-stack experience across Angular, TypeScript, Python, FastAPI, distributed systems, and developer platform engineering
• write clean, functional code and unit tests
• conduct thorough code reviews
• debug and resolve software issues in development and production environments
• coordinate with cross-functional team members to estimate timelines and deliver according to specifications

Software Engineer – AI

• Define and execute the vision, strategy, and roadmap for AI, automation, and intelligent workflows across HR
• Identify opportunities to improve employee experiences, decision-making, and operational effectiveness through AI-enabled solutions
• Assess current-state capabilities, design future-state experiences, and develop strategies that accelerate transformation
• Translate enterprise priorities into scalable products, platforms, and capabilities that create value across HR
• Drive the development of reusable AI, automation, orchestration, and workflow capabilities that support enterprise-wide adoption
• Establish product strategies that leverage vendor platforms while identifying opportunities for differentiated, custom-built solutions
• Evaluate emerging technologies, AI platforms, automation tools, and data capabilities to determine optimal solutions and investments
• Own product vision, roadmap prioritization, business cases, and value realization, delivering measurable business outcomes
• Partner across HR, Technology, Engineering, Architecture, and Data Science to deliver innovative, user-centric solutions and drive adoption
• Establish governance, operating models, success metrics, and responsible AI practices that balance innovation, risk, compliance, and sustainable growth

Senior Lead Product Manager – Agentic AI, Automation

• Design and deploy ML/DL models for robotics, computer vision, and Physical AI applications.
• Optimize models for real-time, edge, and scalable AI environments.
• Integrate perception, planning, and decision-making systems across AI platforms.
• Build scalable data pipelines and streaming architectures for CV, IoT, robotics, and multimodal data.
• Develop reusable datasets and feature engineering pipelines.
• Ensure data quality, observability, and efficient data movement for AI workloads.
• Design and maintain AI platform tools, frameworks, and infrastructure supporting the ML lifecycle.
• Implement CI/CD, deployment, monitoring, and platform automation capabilities.
• Optimize GPU/CPU resource utilization for performance, scalability, and cost efficiency.
• Implement security, governance, and compliance best practices.
• Define KPIs, evaluation frameworks, and model performance metrics.
• Lead experimentation, benchmarking, and A/B testing initiatives.
• Use platform insights and user feedback to drive continuous improvement.
• Partner with data science, robotics, CV, platform, and business teams to deliver scalable AI solutions.
• Translate business requirements into technical AI capabilities.
• Collaborate across teams to align platform innovation with organizational goals.
• Mentor engineers and drive engineering and MLOps best practices.

Senior AI Engineer – Physical AI

Machine Learning Engineer

• Own technical direction of the ML Platform — feature store, model hosting and serving, experimentation, training infrastructure — driving architectural decisions around scalability, reliability, latency, and cost
• Lead design and delivery of large-scope platform initiatives from conception through production, coordinating across ML, data, and infrastructure teams
• Identify and resolve systemic technical challenges: online/offline feature parity, model deployment friction, experimentation velocity, GPU utilization, cross-team dependencies
• Set and maintain a high engineering quality bar through hands-on code contributions, design reviews, and mentorship of platform and ML-adjacent engineers
• Partner with ML engineering, data science, product, and platform leadership to translate ML strategy into technical roadmaps
• Define the paved paths ML teams use to ship models safely — from feature registration through canary rollout, monitoring, and rollback
• Leverage AI-augmented development tools to increase development velocity and code quality

Staff Machine Learning Engineer

• Develop software consistent with Cisco’s ‘Design Thinking Principles’
• Serve as a key driver in the evolution of our AI ecosystem
• Tackle high-impact technical challenges such as optimizing LLM token usage
• Build, integrate, and maintain AI agents and features within the Circuit platform
• Continuously monitor the AI landscape to stack-rank and integrate new models from vendors
• Lead the delivery of high-quality design features from initial concept through to production

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