Role Description We are seeking a motivated and talented individual to join us for a 12-week summer internship within our Development department. This internship will focus on integrating AI tools (e.g., ChatGPT Enterprise / similar LLM platforms) into existing team workflows to reduce manual reporting effort, improve consistency, and accelerate market and project insights. Internships at esVolta aim to offer students industry exposure and hands-on experience. Core Responsibilities - Identify opportunities where AI can reduce effort and improve clarity in recurring stakeholder reporting. - Build a repeatable workflow that can support quarterly market reporting with minimal manual effort. - Prototype AI-driven checks to support QA/QC of budget files and submissions, including consistency checks, anomaly detection, and completeness reviews. - Perform due diligence on investment portfolios. - Craft detailed and informative presentations for management. Qualifications - Currently pursuing a bachelor’s or master’s degree in computer science, engineering, finance, economics, etc. - An interest in the energy sector and US power markets. - Strong analytical thinking and comfort working with ambiguous problems. - Effective communication (verbal, written, and presentation) skills. - Excellent analytical and quantitative skills. - Strong interpersonal skills with the ability to effectively work within multi-disciplinary project teams. - Strong organizational skills and attention to detail. - Experience using LLM tools (ChatGPT, Gemini, Claude, etc.) and interest in applying them to real business workflows. - Familiarity with basic automation concepts (APIs, integrations, workflow tools) and/or prompt engineering. Requirements - The hourly rate for this position is $30.00 per hour. - 40-hour work week. - Flexible; option to work-from-home with periodic office visits for in-person engagement or to work from company offices in Newport Beach. - Willingness to be remotely based and ability to travel to company offices and project sites. Benefits - esVolta is an Equal Opportunity Employer. - We celebrate all forms of diversity and are committed to creating an inclusive environment for all employees. - We ensure that individuals with disabilities are provided reasonable accommodation to participate in the hiring process, perform essential job functions, and receive other benefits and privileges of employment.

• Own end-to-end development of LLM features: problem framing, data prep, prototyping, offline/online evaluation, deployment, and monitoring. • Build retrieval-augmented generation (RAG) pipelines with vector search (e.g., FAISS, Pinecone, OpenSearch/KNN) and document orchestration. • Implement prompt strategies, tool use/function calling, and guardrails for safety, bias, and privacy. • Integrate models in production services (REST/GraphQL/gRPC), including auth, rate limiting, and observability. • Stand up evals and experiment frameworks (A/B tests, golden sets, regression suites) with clear success metrics. • Optimize for latency, cost, and quality: prompt compression, caching, model selection, fine-tuning/LoRA, distillation where appropriate. • Collaborate with DevOps/MLOps/Platform to automate CI/CD, data/version management, and feature flags. • Embed with CX/Support to mine tickets, chats, and call transcripts; convert VOC into training/eval datasets and backlog priorities. • Instrument user journeys and define online/offline evals (win rate, hallucination rate, TTR, CSAT/NPS); run A/B tests and ship iterative improvements. • Build feedback loops (thumbs-up/down, rationale capture, escalation) and human-in-the-loop fallbacks that protect quality. • Own reliability and UX details that matter for customers: latency budgets, safe fallbacks, clear handoff to human agents, accessibility. • Partner with Trust/Legal/Security to ensure privacy-by-design and compliant data handling; implement guardrails and red-team mitigations.

About the Role We’re hiring a developer with deep, hands-on experience building with MCP and ChatGPT Apps. This is not a general AI role. You should already be comfortable working inside these ecosystems, even if that experience comes from building, testing, or experimenting with your own projects. This is a remote or in-person role (Austin, TX). You’ll be responsible for creating production-grade AI applications, iterating quickly, and pushing the boundaries of what MCP and ChatGPT Apps can do. What You’ll Do - Build, deploy, and maintain MCP-based applications - Develop and optimize ChatGPT Apps using tools, structured outputs, and workflows - Design AI-native product experiences from the ground up - Rapidly prototype and test new ideas using MCP and ChatGPT environments - Use Claude Code as part of your development workflow - Improve performance, reliability, and usability of AI-driven features - Collaborate on product direction and technical architecture What We’re Looking For - Someone who has already spent serious time inside MCP + ChatGPT App environments - Builders who experiment, ship quickly, and learn by doing - Developers who understand both the technical and product side of AI apps - People who can operate with high ownership and minimal oversight

About Our Client Servant is partnering with a forward-thinking organization focused on helping teams work smarter, not harder. By combining thoughtful strategy, intuitive tools, and a people-first mindset, enabling organizations to optimize how work gets done—improving efficiency, clarity, and outcomes across the business. With a strong emphasis on collaboration and continuous improvement, our client partners closely with its customers to solve real-world challenges and deliver practical, scalable solutions. The team values curiosity, ownership, and impact, and is committed to building products and experiences that genuinely support the way people work today. As our client continues to grow, they are investing in talented, mission-driven individuals who want to shape the future of work and make a meaningful difference for customers and teammates alike. Role Summary Our client is building the world’s first Human-Led AI Orchestration Layer—a platform designed to keep humans firmly in control of AI through clarity, accountability, and execution via our proprietary Action Points. As an AI Engineer, you will design and implement the intelligence layer that translates raw information into human-directed outcomes. You will work across LLMs, agentic workflows, and AI pipelines to ensure AI remains a tool governed by human intent, not an autonomous system. Everything you build is expected to be revenue-ready, secure, and production-grade. Key Responsibilities AI & Intelligence Engineering - Design and implement AI-driven workflows that generate actionable, human-directed insights. - Build and optimize LLM-powered systems for summarization, recommendation, classification, and orchestration. - Implement agentic AI patterns that operate under explicit human guardrails and approval flows. - Translate unstructured data into structured Action Points™ aligned with user goals. - Develop and maintain prompt architectures and evaluation frameworks for consistent AI output quality. - Architect and develop semi-autonomous AI agents with mandatory human-in-the-loop control points, safety guardrails, and review checkpoints. Voice to Text - Design and implement AI-driven voice workflows that generate actionable, human-directed insights. - Architect real-time speech-to-text pipelines for AI control, command execution, and Action Point generation. - Implement low-latency voice ingestion using Azure Speech SDK for real-time transcription, intent detection, and multilingual support. - Ensure voice inputs are securely processed, auditable, and aligned with human authorization and approval flows. - Translate spoken input into structured, human-directed Action Point that govern downstream AI agents. Integration & Deployment - Deploy AI services using FastAPI and integrate them securely with backend systems. - Collaborate with frontend and backend engineers to expose AI capabilities via secure APIs. - Ensure AI systems scale reliably in cloud environments (Azure-based). Performance, Ethics & Governance - Optimize inference latency, throughput, and cost efficiency. - Implement observability, logging, and monitoring for AI workflows. - Apply responsible AI principles: transparency, auditability, and human override by design.