ai solutions architect

VGA Holdings

<p><b>About the Role </b></p><p>We are looking for an experienced AI Solutions Architect / Developer to join our team and lead the design, implementation, and continuous improvement of AI-powered features within our education platform. This is a hands-on technical role requiring someone who can work independently, review existing AI implementations, identify architectural improvements, and build scalable AI solutions from the ground up.</p><p>The ideal candidate is comfortable working across the entire AI stack&mdash;from prompt engineering and RAG pipelines to model training, embeddings, vector databases, backend integration, and production deployment.</p><p><b>Key Responsibilities:</b></p><ul><li>Review and improve our existing AI implementation.</li><li>Identify architectural issues, performance bottlenecks, and security vulnerabilities.</li><li>Design efficient AI workflows that minimize token usage and API costs.</li><li>Build and maintain Retrieval-Augmented Generation (RAG) pipelines.</li><li>Integrate Large Language Models (LLMs) such as Claude, GPT, Gemini, Llama, Qwen, or similar models into our in-house platform.</li><li>Design prompt engineering strategies and evaluation frameworks. Implement human-in-the-loop feedback systems for continuous AI improvement.</li><li>Build and maintain embedding pipelines and vector databases.</li><li>Develop AI services, APIs, and backend integrations.</li><li>Evaluate new AI technologies and recommend improvements.</li><li>Document AI architecture, workflows, implementation details, and best practices. Collaborate with software developers, QA engineers, and product teams to deliver production-ready AI solutions.</li><li>Troubleshoot production AI issues and optimize response quality, latency, and cost.</li></ul><p><b>Experience:</b></p><ul><li>5+ years of software development experience</li><li>with at least 2 years of hands-on experience building production AI systems.</li></ul><p><b>Required Skills: </b></p><p><b>Artificial Intelligence</b></p><ul><li>Large Language Models (LLMs)</li><li>Prompt Engineering</li><li>Retrieval-Augmented Generation (RAG)</li><li>Embeddings</li><li>Vector Databases</li><li>Semantic Search</li><li>AI Evaluation</li><li>AI Guardrails</li><li>AI Safety</li><li>AI Observability</li></ul><p><b>Model Development </b></p><ul><li>Fine-tuning</li><li>LoRA / QLoRA</li><li>Model Training</li><li>Dataset Preparation</li><li>Synthetic Data Generation</li><li>Model Evaluation</li><li>Reinforcement Learning from Human Feedback (RLHF) knowledge is a plus</li></ul><p><b>AI Frameworks</b></p><ul><li>Experience with one or more:</li><li>LangChain</li><li>LlamaIndex</li><li>DSPy</li><li>CrewAI</li><li>AutoGen</li><li>Semantic Kernel</li></ul><p><b>Vector Databases</b></p><p>Experience with one or more:</p><ul><li>pgvector</li><li>Pinecone</li><li>Weaviate</li><li>Qdrant</li><li>Milvus</li><li>ChromaDB</li></ul><p><b>Backend Development</b></p><p>Experience with:</p><ul><li>Python (preferred)</li><li>FastAPI</li><li>REST APIs</li><li>PostgreSQL</li><li>SQL</li><li>Docker</li><li>Git</li></ul><p><b>Cloud &amp; Infrastructure</b></p><p>Experience with:</p><ul><li>AWS</li><li>Google Cloud</li><li>GPU deployments</li><li>Docker</li><li>Kubernetes (preferred)</li></ul><p><b>What We're Looking</b> <b>For</b>:</p><p>The successful candidate should be able to:</p><ul><li>Work independently with minimal supervision.</li><li>Take ownership of AI architecture and implementation.</li><li>Review existing code and improve it.</li><li>Identify bugs before they become production issues.</li><li>Write clean, maintainable, and well-documented code.</li><li>Think critically and propose better technical solutions.</li><li>Communicate technical concepts clearly with both technical and non-technical stakeholders.</li><li>Work effectively both independently and within a collaborative development team.</li><li>Stay up to date with the rapidly evolving AI ecosystem.</li></ul><p><b>Nice to Have:</b></p><ul><li>Experience building AI products, preferably for Education (EdTech).</li><li>Experience with multi-agent AI systems. Knowledge of child psychology or educational assessment.</li><li>Experience deploying open-source LLMs locally.</li><li>Experience with Hugging Face ecosystem.</li><li>Experience building AI evaluation pipelines. Knowledge of MCP (Model Context Protocol). Experience with speech recognition (Whisper), OCR, or computer vision.</li></ul><p>Interested Applicants can share their CV via;</p><ul><li>email: info@vgaholdings.com</li><li>WhatsApp: +973 6663 3334 <b>(NO CALLS)</b></li></ul><p>Work Location: In person</p>

AI Solutions Architect

General Dynamics Information Technology

<div></div><div><div><div>Clearance Level
<div>None</div>
</div><div></div><div>Category
<div>Data Science and Data Engineering</div>
</div><div></div><div>Location
<div>Falls Church, Virginia</div>
<i>(</i><i>Hybrid Workplace</i><i>)</i>
</div><div>
</div></div><div><div>Key Skills For Success
</div><div><p>AI Frameworks</p>
</div><div><p>AI Ops</p>
</div><div><p>Model Evaluation</p>
</div></div><div></div><div><div><div><div><div><div>
</div></div></div><div><h5 class="jobSectionHeader"><b>REQ#:</b><b> </b><b>RQ217980</b></h5>
<h5 class="jobSectionHeader"><b>Public Trust:</b><b> </b><b>None</b></h5>
<h5 class="jobSectionHeader"><b>Requisition Type:</b><b> </b><b>Pipeline</b></h5>
<h5 class="jobSectionHeader"><b>Your Impact</b></h5>
<p>Own your opportunity to be at the center of GDIT&rsquo;s business operations. Make an impact by collaborating across functions to make mission success achievable.</p>
<h2 class="jobSectionHeader"><b>Job Description</b></h2>
<div><p>As an <b>Agentic </b><b>AI Engineer,</b> you will be responsible for designing, developing and deploying AI models, algorithms and systems to enhance productivity, decision-making and automation within the organization.</p>
<p></p><p>If you have 1+ years of experience developing products or functional prototypes using RAG and agentic AI technologies, we want to speak with you!</p><br>
<p><br>
<b>MEANINGFUL WORK AND PERSONAL IMPACT</b>
<br>
As an <b>Agentic </b><b>AI Engineer,</b> the work you&rsquo;ll do at GDIT will be impactful to the mission.
</p><ul><li><p>Architect and implement production-grade multi-agent AI solutions with modern orchestration frameworks, enabling reliable, transparent, and secure agentic workflows</p>
</li><li><p>Build and maintain end-to-end agentic AI pipelines, from data ingestion and embedding to deployment and continuous evaluation, optimized for reusability and scalability</p>
</li><li><p>Develop, test, and deploy internal AI applications that enhances people-powered, AI-enabled productivity</p>
</li><li><p>Provide unified observability with logging, metrics, and alerts and analyze agent runtime behavior to tune latency, accuracy, and cost in production</p>
</li><li><p>Integrate agentic AI services with existing enterprise systems and uphold AIOps practices for consistent deployment and scaling</p>
</li><li><p>Collaborate with cross-functional teams including data scientists, software engineers, and product / service owners to align AI projects with business goals</p>
</li><li><p>Must stay updated on emerging AI related technologies and recommend improvements to existing AI systems</p><br>
</li></ul><p><br>
<b>WHAT YOU&rsquo;LL NEED TO SUCCEED</b>
<br>
Bring your expertise and drive for innovation to GDIT. The <b>Agentic</b> <b>AI Engineer </b>must have:
</p><ul><li><p><b>Education</b>: Bachelor&rsquo;s Degree in Computer Science, Computer Engineering, Data Science or a related field</p>
</li><li><p><b>Experience</b>:</p>
</li><li><p><b>5+ years of experience in AI and machine learning, including hands-on experience with designing, developing, and deploying AI models and systems.</b></p>
</li><li><p><b>1+ years of experience developing products or functional prototypes using RAG and agentic AI technologies.</b></p>
</li><li><p><b>Must have designed and/or implemented hands-on an agentic workflow solution (not just simply prompt engineering to LLMs)</b></p>
</li><li><p><b>Role requirements</b>:</p>
</li><li><p>Proven track record of delivering end-to-end AI projects and successfully integrating AI solutions into business processes.</p>
</li><li><p>Proficiency in programming languages such as Python, R, or Java, and deep understanding of machine learning frameworks like TensorFlow or PyTorch.</p>
</li><li><p>Strong hands-on experience with MCP, LangGraph, LlamaIndex, or similar agentic frameworks.</p>
</li><li><p>Deep understanding of prompt or context engineering, tool definition, and state management for agents.</p>
</li><li><p>Experience with cloud computing platforms, such as Azure (Preferred), OCI, AWS, or Google Cloud, including AI services like Azure AI Foundry, Bedrock, or Vertex AI.</p>
</li><li><p>Strong background in working with large datasets and performing data preprocessing, feature engineering, and model evaluation.</p>
</li><li><p><b>Preferred Skills and Abilities:</b> Masters degree. Advanced coursework or a Certification in AI, Machine Learning or related areas desirable</p>
</li><li><p><b>Location: Hybrid 3 days in Falls Church office</b></p>
</li><li><p>US Persons required</p><br>
</li></ul><div><br>
GDIT IS YOUR PLACE
<br>
At GDIT, the mission is our purpose, and our people are at the center of everything we do.
<ul><li>Growth: AI-powered career tool that identifies career steps and learning opportunities
</li><li>Support: An internal mobility team focused on helping you achieve your career goals
</li><li>Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
</li><li>Community: Award-winning culture of innovation and a military-friendly workplace
</li></ul><br>
OWN YOUR OPPORTUNITY
<br>
Explore a career in data science and engineering at GDIT and you&rsquo;ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.
</div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Work Requirements</b></h3>
</div></div><div></div><div><div>Years of Experience
<p>5 + years of related experience</p>
<ul><li>may vary based on technical training, certification(s), <b><i>or</i></b> degree</li></ul>
</div><div></div><div>Certification
</div><p></p><div>Travel Required
<p>Less than 10%</p>
</div></div></div></div><div><h3 class="jobSectionHeader"><b>Salary and Benefit Information</b></h3>
<p>The likely salary range for this position is $169,604 - $229,464. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.
</p>
<h3 class="jobSectionHeader"><b>Our Identity Verification Process</b></h3>
<p>As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.</p>
<h3 class="jobSectionHeader"><b>About Our Work</b></h3>
<div></div><p>We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.</p>
<p>Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc.</p>
<p><i>Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans</i></p></div></div></div></div>

Agentic AI Engineer

EPAM Systems

<div><p>We're looking for a <b>Lead AI Engineer </b>to join our team in <b>Doha, Qatar,</b> in an <b>onsite working mode</b>.</p><p>
In this role, you will lead the design and implementation of AI-driven strategies, architectures and operating models, enabling engineering teams to transition to spec-driven and agentic AI delivery methods. This is a critical position to influence and drive AI-assisted development, ensuring scalable implementations, governance and measurable business outcomes. Your expertise will shape AI adoption across the organization, balancing innovation with compliance, security and operational integrity.</p><p><b>
Responsibilities</b></p><ul><li>
Architect and deploy token-efficient AI search and retrieval systems optimized for cost, relevance and performance</li><li>
Advise on AI adoption strategies, including when to apply RAG, agents, copilots or traditional engineering approaches</li><li>
Define and implement spec-driven development practices with governance and reusable standards</li><li>
Design KPIs to measure productivity gains, quality improvements and AI adoption maturity</li><li>
Build end-to-end AI pipelines, including embeddings, vector stores, retrieval layers, LLM integrations and streaming inference</li><li>
Develop operational strategies for agentic systems, including rollout governance, versioning and observability</li><li>
Partner with product owners and engineering leads to define AI adoption roadmaps and enable workforce capability uplift</li><li>
Drive training, playbooks and mentorship to accelerate workforce readiness in AI-enabled engineering workflows</li><li>
Implement responsible AI practices, ensuring compliance with security, safety and ethical guidelines</li></ul><p><b>
Requirements</b></p><ul><li>
Bachelor's degree in Computer Science, Software Engineering or related field</li><li>
4+ years of experience building production AI systems or 2+ years in production-level LLM/RAG solutions</li><li>
Proven track record leading AI transformations, strategy design and adoption initiatives</li><li>
Deep expertise in RAG architectures: embeddings, vector DBs, retrieval strategies</li><li>
Strong proficiency with Python, familiarity with Java and API protocols (REST/gRPC)</li><li>
Experience with agent frameworks and implementing agentic workflows in enterprise software delivery</li><li>
Practical knowledge of Kubernetes, cloud services, CI/CD pipelines and deployment automation</li><li>
Hands-on experience in integrating LLM providers and self-hosted models into scalable architectures</li><li>
Knowledge of AI observability, testing frameworks, model versioning and prompt governance</li></ul><p><b>
We offer</b></p><ul><li>
Private healthcare and life insurance</li><li>
End of service gratuity</li><li>
Annual air travel tickets for expatriates</li><li>
Corporate Programs including Employee Referral Program with rewards</li><li>
Learning and development opportunities including in-house training and coaching, professional certifications, and courses</li></ul></div>

Lead AI Engineer

Bazzle Balloons

<p>we&rsquo;re looking for an AI <b>Agentics Lead</b> to lead the design, development, and deployment of agentic AI systems and scalable AI/ML infrastructure. This role sits at the intersection of AI engineering and client delivery &mdash; ideal for an experienced MLE or AI engineer who can go deep on agent orchestration, LLM systems, and production automation, while also working directly with clients to understand their business challenges and translate them into deployable agentic workflows.</p><p>You will own the full lifecycle: partnering with clients and end-users to surface problems and define requirements, architecting and building agents, tools, and integrations tailored to those needs, deploying solutions into client and internal environments, and ensuring their ongoing reliability, quality, and measurable business impact.</p><p><b>Key Responsibilities</b></p><ul><li>Design, build, and deploy custom AI skills, agents, and automated workflows tailored to client and internal use cases, from single-task agents to complex orchestrated workflows.</li><li>Evaluate, select, and route across LLMs (e.g., <b>Anthropic Claude, OpenAI, Google Gemini, and open-weight models</b>) to perform domain-specific tasks with high accuracy and reliability.</li><li>Develop integrations and connectors between AI platforms and client systems (<b>CRM, ERP, file systems, Slack, email, etc.</b>) to embed AI into existing workflows.</li><li>Lead discovery with clients and end-users to surface business challenges, define requirements, and map them into agentic workflow and solution designs.</li><li>Lead hands-on deployment of AI solutions into client environments, working alongside internal teams to train users, gather feedback, and iterate on solutions.</li><li>Architect agent orchestration patterns (sequential, parallel, hierarchical, supervisor/worker) and design <b>agent-to-agent (A2A)</b> communication and coordination.</li><li>Build and integrate tools, function-calling, and <b>MCP (Model Context Protocol)</b> servers and clients to connect agents to data sources, APIs, and enterprise systems.</li><li>Design memory, state, and context-management strategies (short-term, long-term, and retrieval-augmented) for long-running and stateful agents.</li><li>Use LLMs efficiently: optimize token usage, context windows, caching, and model tiering to balance quality against cost and speed.</li><li>Establish evaluation frameworks (eval harnesses, regression suites, LLM-as-judge, golden datasets) to measure and protect agent quality over time.</li><li>Implement guardrails, output validation, and human-in-the-loop checkpoints to manage hallucination, error handling, and failure modes.</li><li>Build observability into agentic systems &mdash; tracing, logging, cost/token monitoring, and performance metrics &mdash; and use it to debug and continuously improve.</li><li>Apply responsible-AI and security practices: prompt-injection defense, PII/data handling, access controls, and auditability &mdash; especially important given the sensitivity of client data.</li><li>Mentor and review the work of other engineers; raise the team's overall agentic and LLM capability.</li><li>Stay current on emerging AI tools, platforms, and capabilities to continuously expand the activation toolkit and identify new deployment opportunities.</li><li>Collaborate with Machine Learning Engineers to determine transition points for full-scale software engineering product builds.</li><li>Establish value measurement and realization tracking frameworks to quantify productivity gains, time savings, and business impact for each deployed solution.</li><li>Collaborate with the AI Strategy team to translate roadmap recommendations into deployable activation plans.</li></ul><p><b>Qualifications</b></p><ul><li>5+ years of experience in AI/ML engineering, solutions architecture, automation, or a related technical delivery role</li><li>Hands-on proficiency with AI platforms such as <b>Claude, ChatGPT, Copilot, Gemini,</b> etc. including prompt engineering, skill/agent/workflow creation, and API integration</li><li>Experience building and deploying AI-powered workflows, automations, or agentic systems in production environments</li><li>Strong skills in <b>Python, JavaScript/TypeScript, or similar languages</b>; familiarity with REST APIs, webhooks, and enterprise integration patterns</li><li>Demonstrated ability to work directly with clients and end-users to understand requirements, gather feedback, and iterate on solutions</li><li>Experience with CRM, ERP, or enterprise productivity platforms (<b>Salesforce, HubSpot, NetSuite, Slack, Microsoft 365</b>, etc.) and their integration capabilities</li><li>Strong communication skills with the ability to train non-technical users and document solutions clearly</li><li>Curiosity-driven mindset with a passion for discovering novel applications of AI across diverse business contexts</li></ul><p><b>Nice To Have</b></p><ul><li>Experience with RAG, vector databases (e.g., <b>pgvector, Pinecone, Weaviate</b>), and retrieval/memory design.</li><li>Experience with cloud platforms (<b>AWS, GCP, or Azure</b>) and deploying/operating AI systems (<b>containers, CI/CD</b>).</li><li>Familiarity with LLM observability and evaluation tooling (e.g., <b>LangSmith, Langfuse, Arize,</b> or similar).</li><li>Background in consulting, professional services, or client-facing delivery.</li><li>Exposure to security, compliance, or responsible-AI practices.</li><li>Experience in proposal development and scoping for activation engagements, including effort estimation and solution design.</li><li>Author AI Playbooks documenting deployed solutions, operating procedures, prompt libraries, and best practices for ongoing client use.</li></ul><p>Application Question(s):</p><ul><li>How many years of experience in AI/ML engineering, solutions architecture, automation, or a related technical delivery role</li><li>Do you have Hands-on proficiency with AI platforms such as Claude, ChatGPT, Copilot, Gemini, etc. including prompt engineering, skill/agent/workflow creation, and API integration?</li><li>How many years of experience in Python, JavaScript/TypeScript, or similar languages; familiarity with REST APIs, webhooks, and enterprise integration patterns</li><li>How many yearss of experience do you have in  CRM, ERP, or enterprise productivity platforms (Salesforce, HubSpot, NetSuite, Slack, Microsoft 365, etc.) and their integration capabilities</li><li>Please mentioned your Degree.</li><li>How many years of experience do you have  with RAG, vector databases (e.g., pgvector, Pinecone, Weaviate), and retrieval/memory design.</li></ul><ul><li>How many years of experience do you have with cloud platforms (AWS, GCP, or Azure) and deploying/operating AI systems (containers, CI/CD).</li></ul><ul><li>How many years of experience do you have with LLM observability and evaluation tooling (e.g., LangSmith, Langfuse, Arize, or similar)</li><li>Current Salary?</li><li>Expected Salary</li><li>Notice Period</li></ul><p>Experience:</p><ul><li>AI Agentic: 6 years (Required)</li></ul><p>Work Location: Remote</p>

AI Agentic Lead

NVIDIA

<div>
 NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production &mdash; over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we're looking for the engineer to lead that charge. In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows, driving initiatives from concept to deployment. If you combine deep technical expertise with a hands-on approach and an aim to push the boundaries of what's possible, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed!
 <br/>
 <br/>
 <strong>
  What You'll Be Doing
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   LLM-Powered Validation Pipelines: Design and deploy AI systems that make post-silicon validation faster, smarter, and more scalable across semiconductor environments. You're not maintaining what exists, you're building what comes next.
  </li>
  <li>
   Cross-Team AI Integration: Work directly with multi-functional engineering teams across the organization to identify where AI can eliminate friction, and then build the solution. Your output will be felt across teams, products, and generations of silicon.
  </li>
  <li>
   Technology Scouting &amp; Evaluation: Evaluate emerging AI frameworks and architectures before the rest of the industry catches on. Be the person who spots what's worth adopting, and makes the case for it.
  </li>
  <li>
   Impact Measurement &amp; Continuous Improvement: Build the data systems that prove what's working. Establish clear, quantitative indicators of AI impact, close performance gaps, and drive iteration across the org to turn insight into lasting improvement!
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Need To See
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services.
  </li>
  <li>
   2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end &mdash; from prototype through production deployment.
  </li>
  <li>
   Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
  </li>
  <li>
   Experience working within a silicon development environment, with exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing/power analysis.
  </li>
  <li>
   Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).
  </li>
  <li>
   Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction.
  </li>
  <li>
   Proven track record to balance multiple concurrent projects and apply excellent problem-solving, communication, and teamwork skills.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Ways To Stand Out From The Crowd
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience debugging complex system-level issues involving HW/SW interactions, including leadership or ownership in driving root cause analysis of silicon or feature-level issues.
  </li>
  <li>
   Ability to translate innovative AI research into practical, high-impact production tools.
  </li>
  <li>
   Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.
  </li>
  <li>
   Experience with building and deploying orchestration agents managing hundreds to thousands of tools.
  </li>
  <li>
   Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow, and hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.
   <br/>
   <br/>
  </li>
 </ul>
 Our team is at the forefront of silicon innovation, advancing groundbreaking technologies. We offer a dynamic work environment where your contributions will directly impact the company's success. Join us to advance your career in a role where you can truly make a difference. With competitive salaries and a generous benefits package, we are widely considered one of the technology industry&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us, and due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!
 <br/>
 <br/>
 Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
 <br/>
 <br/>
 You will also be eligible for equity and benefits.
 <br/>
 <br/>
 Applications for this job will be accepted at least until August 1, 2026.
 <br/>
 <br/>
 This posting is for an existing vacancy.
 <br/>
 <br/>
 NVIDIA uses AI tools in its recruiting processes.
 <br/>
 <br/>
 NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
 <br/>
 <br/>
 , , JR2018179
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 <br/>
</div>


Applied AI Engineer

University of California - San Francisco

<div><p>Certain terms and conditions of employment for this position, including the rate of pay, benefits, etc., are currently subject to negotiation with the appropriate union.
</p><p>The Oracle Cloud AI Architect is responsible for designing, implementing AI-enabled solutions, analytics, automation, and enterprise applications across Oracle Cloud Human Capital Management (HCM), Supply Chain Management (SCM), Financials (FIN), Procurement, and related systems. This role partners with business stakeholders, operational leaders, and technical teams to design and optimize scalable solutions that improve business operations, decision-making, and user experience across the enterprise.
</p><p>The incumbent applies advanced knowledge of Oracle Cloud architecture, enterprise business processes, data management, and AI-enabled technologies to support intelligent automation, predictive analytics, reporting, workflow optimization, and enterprise data initiatives. Responsibilities include leveraging Oracle Cloud technologies such as OTBI, BI Publisher, Smart View, Fusion Data Intelligence (FDI), Fusion Analytics Warehouse (FAW), Oracle AI services, and related analytics platforms to develop integrated and secure enterprise solutions aligned with organizational goals.
</p><p>This role collaborates closely with Business Systems Analysts, ERP functional teams, developers, integration teams, and leadership to support system enhancements, enterprise integrations, data governance, testing, upgrades, and continuous improvement initiatives. The position also evaluates emerging Oracle Cloud and AI capabilities, promotes self-service analytics and automation, and supports operational excellence through scalable, compliant, and data-driven enterprise solutions.
</p><p>This position includes regular onsite work, typically 1&ndash;3 days per month. The exact schedule and frequency may be adjusted as needed to meet departmental and operational demands<br>
</p><p></p><p><b>Department Overview
</b></p><p>The Business Informatics &amp; Analysis team is responsible for delivering functional expertise, business process analysis, and application support across the enterprise&rsquo;s Oracle Cloud ERP ecosystem. This team partners with business stakeholders, technical, and cross-functional teams to ensure that Oracle ERP modules&mdash;such as Finance, Procurement, Projects, Research, Supply Chain, and Human Capital Management (HCM)&mdash;are effectively configured, optimized, and aligned with organizational objectives.
</p><p>The team provides both strategic and operational support, including requirements gathering, solution design, process improvement, system configuration, testing, reporting, and training. Their work ensures that Oracle Cloud ERP and the boundary systems it integrates with enable accurate, efficient, and scalable business operations.</p></div><p></p>
<br><div><p><b>REQUIRED QUALIFICATIONS
</b></p><ul><li>Bachelor's degree in a related area and/or equivalent experience/training.
</li><li>5+ years of experience in business transformation, value engineering, strategy, or enterprise advisory roles, preferably in healthcare or higher education environments.
</li><li>5+ experienced with Oracle Fusion applications, analytics, or AI platforms
</li><li>3+ years of dimensional and relational data modeling experience
</li><li>2+ years building and delivering LLM/GenAI solutions
</li><li>Ability to understand and model complex knowledge-intensive processes Oracle ERP data structures and business processes (Finance, SCM, Research or HCM)
</li>Familiarity with highly complex data quality and governance issues and requirements.<br>
<li>
</li></ul><p></p><p><b>PREFERRED QUALIFICATIONS
</b></p><ul><li>Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization. Interpersonal and communications skills to work with both technical and non- technical personnel at various levels in the organization.
</li><li>3+ years of experience in relational database, SQL, or system development life-cycle project; and/or equivalent experience/training.
</li><li>1+ year of experience in an organization comparable to UCSF in terms of budget, size, complexity, scope of operation, and accounting systems
</li><li>Knowledge of supply chain, human capital management, or finance systems and processes within a healthcare or higher education environment
</li><li>Certifications
</li><li>Oracle Certifications
</li><li>Lean Six Sigma Black Belt (LSSBB)
</li><li>Project Management Professional (PMP)
</li><li>Certified Business Analysis Professional (CBAP)</li></ul></div>
<br><div><div><b>About UCSF<br>
</b></div><div></div><br>
<div>The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences. We bring together the world&rsquo;s leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells.<br>
</div><div></div><br>
<div><b>Pride Values<br>
</b></div><div></div><br>
<div>UCSF is a diverse community made of people with many skills and talents. We seek candidates whose work experience or community service has prepared them to contribute to our commitment to professionalism, respect, integrity, diversity and excellence &ndash; also known as our PRIDE values .<br>
</div><div></div><br>
<div>In addition to our PRIDE values, UCSF is committed to equity &ndash; both in how we deliver care as well as our workforce. We are committed to building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for the provision of culturally competent education, discovery, and patient care. Additional information about UCSF is available here .<br>
</div><div></div><br>
<div>Join us to find a rewarding career contributing to improving healthcare worldwide.<br>
</div><div></div><br>
<div><b>Equal Employment Opportunity<br>
</b></div><div></div><br>
<div><i>The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.<br>
</i></div><div></div><br>
<div><div><b>Salary Information<br>
</b></div><div></div><br>
<div>The final salary and offer components are subject to additional approvals based on UC policy.<br>
</div><div></div><br>
<div>Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement.<br>
</div><div></div><br>
<div>To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html</div></div></div><div></div>

Oracle AI Forward Engineer

American business solutions inc

<div><h2 class="jobSectionHeader"><b>Required Skills</b></h2>
<p>Undergraduate degree in computer science, data science, artificial intelligence or related field required.</p>
<p>1 year of proven experience with establishing proof of concept success criteria and evaluating AI solutions against criteria</p>
<p>2 years of hands-on experience with ChatGPT, Microsoft Copilot, and comparable generative AI platforms</p>
<p>2 years of experience designing and implementing AI agents and retrieval-augmented generation (RAG) solutions.</p>
<p>1 year of experience using AI-assisted coding tools to accelerate development, testing, debugging, and documentation.</p>
<p>1 year of experience defining AI use case success criteria, key performance indicators (KPIs) and production monitoring measures for AI use cases.</p>
<p>1 year of experience building dashboards and reporting for AI adoption, performance, cost, risk, and operational outcomes.</p>
<p>1 year of hands-on experience integrating AI capabilities with Azure and AWS.</p>
<h2 class="jobSectionHeader"><b>Preferred Skills</b></h2>
<p>Background in a variety of programming languages and principals.</p>
<p>Familiarity with the foundations of artificial neural networks (ANNs), transformers, natural language processing, image classification and time-series data.</p>
<p>Experience with data tools and techniques for storing, retrieving, and cleaning data.</p></div>

Generative AI Engineer(Local to SC)

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