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David Careers

AI/ML Lead with Gemini exp

Posted 11 days ago

united software groupAustin (TX)
Data ScientistsCustom Computer Programming Services

SENIORITY

Lead

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About the role

AI/ML Lead with Gemini Experience
Position: AI/ML Lead with Gemini experience
Location: Austin TX (3 days WFO)
Duration: Long term
Job Description: As an AI Solutions & Success Specialist, you will be at the heart of improving our enterprise digital assistant (DA) experience, which utilizes a suite of internal and external tools including Gemini, ChatGPT, and Copilot. In this role, you will help users get the most out of our AI solutions, identify opportunities for automation, and collaborate with engineering to make every interaction smarter, faster, and more satisfying. This is a pivotal position for someone who thrives in fast-evolving tech environments and wants to shape how AI transforms the employee experience.
Key Responsibilities: User Support & Advocacy
  • Internal User Support: Serve as the primary contact for internal user requests related to AI suites, helping users when automation cannot.
  • Technical Troubleshooting: Investigate and resolve user issues regarding LLM behaviors, ensuring fast, friendly, and accurate responses.
  • Incident Analysis: Identify recurring issues, patterns, and opportunities for product improvement based on support data.
  • Voice of the Customer: Act as a champion for internal users, translating their challenges into actionable insights and enhancement requests for technical teams. AI Knowledge Generation & RAG Pipeline
  • RAG Pipeline Oversight: Oversee the integrity of our Retrieval-Augmented Generation pipelines, ensuring the AI has the correct context to minimize hallucinations.
  • Knowledge Curation: Create and refine internal knowledge articles to improve both chatbot and human support accuracy.
  • Content Governance: Support content governance and taxonomy to ensure better AI retrieval and human accessibility.
  • AI Training: Help refine model prompts, responses, and fallback scenarios using live feedback. Technical Implementation & Connectivity
  • Connector Development: Design and build connectors to integrate the Digital Assistant with internal data sources and third-party tools.
  • MCP Integration: Implement and maintain the Model Context Protocol (MCP) to standardize how AI models interact with data.
  • Platform Management: Manage AI workflows and model performance within Vertex AI and the broader GCP (Google Cloud Platform) environment.
  • Advanced LLM Techniques: Apply techniques such as tool calling, context window management, and prompt engineering to resolve complex technical issues. Governance & Agent Management
  • Agent Lifecycle Management: Review, monitor, and manage the deployment of AI agents to ensure they remain aligned with business objectives.
  • Audit & Compliance: Periodically review agent logs and behaviors to ensure compliance with corporate governance, ethical AI standards, and security policies.
  • Behavior Monitoring: Track "agent drift" and performance decay, implementing corrective measures when agents deviate from their intended logic or safety boundaries. Analytics & Continuous Improvement
  • Impact Analysis: Analyze chatbot and support data to identify high-impact improvement areas within our AI suites.
  • Performance Tracking: Support post-launch performance tracking and monitor user adoption metrics across the enterprise.
  • Optimization: Contribute to prompt and conversation optimization to drive better user engagement and satisfaction.
  • Model Refinement: Collaborate with engineers and Product Managers to improve assistant tone, accuracy, and responsiveness.
Technical Stack & Qualifications General Skills Analytical Problem Solving: A natural ability to deconstruct complex technical failures, identify root causes, and implement systemic fixes rather than temporary workarounds. Exceptional Communication: Strong written and verbal skills; ability to explain highly technical AI concepts (like vector embeddings or context windows) to non-technical stakeholders clearly and empathetically. Adaptability: Comfort working in a "v1.0" environment where tools and protocols change rapidly. Required Technical SkillsAI Tool Fluency: Expert-level familiarity with Generative AI and LLM-based technologies such as ChatGPT, Gemini, and Microsoft Copilot. Cloud & AI Platforms: Proficiency with Google Cloud Platform (GCP) and Vertex AI.LLM Engineering: Deep understanding of RAG pipelines, tool/function calling, and context window management.
Preferred Qualifications: (Bonus) Workflow Automation: Knowledge of n8n or similar workflow automation tools for building event-driven AI integrations. Protocol Expertise: Experience implementing the Model Context Protocol (MCP).
Experience & Education: Bachelor's degree in Information Systems, Computer Science, Business, or equivalent experience.
Experience: 5+ years of professional experience (7+ for senior roles) in IT support, product operations, or digital assistant environments. Process Improvement: Demonstrated experience improving support processes and documentation at scale. Data-Driven: Analytical mindset and comfort with data-driven decision-making. You'll Thrive Here If You…Love helping others and turning feedback into action. Are a proactive self-starter who constantly looks for ways to make things better. Think systematically: you don't just solve one problem, you fix the process behind it. Can collaborate effectively across technical, product, and operations teams. Thanks & Regards, Ranjith Kumar Vemula

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