--- title: "Software Engineering Intern (Summer 2027)" company: "CTGT" company_url: "https://www.remjobs.works/companies/ctgt" url: "https://www.remjobs.works/job/ctgt-software-engineering-intern-summer-2027-0666738f-39dd-46e7-bfe8-2d2cc3cb96b1" apply_url: "https://jobs.ashbyhq.com/ctgt/f657c2f5-125e-42b6-a68a-646bbea3d155" workplace: onsite location: "San Francisco" employment_type: full-time seniority: internship role: software-engineering region: united-states skills: ["aws", "gcp", "javascript", "llm", "python"] date_posted: 2026-06-26T22:03:28.491Z first_seen_by_remjobs: 2026-08-27T09:28:46.110Z --- # Software Engineering Intern (Summer 2027) **CTGT** — San Francisco Apply: https://jobs.ashbyhq.com/ctgt/f657c2f5-125e-42b6-a68a-646bbea3d155 ## About CTGT CTGT is an applied AI research laboratory fundamentally solving the alignment and reliability bottleneck for enterprise AI. For enterprises, especially highly regulated industries, deploying Generative AI is historically a compromise between capability and catastrophic risk. Standard enterprise approaches, such as RAG, fine-tuning, and prompt engineering, operate at the wrong abstraction layer. They are inherently probabilistic, carry massive engineering overhead, and fail to deliver the mathematical certainty required by the Fortune 500. We focus on the science of representation engineering and have productized mechanistic interpretability. By opening the "black box" of neural networks, CTGT has developed a proprietary architecture that intervenes directly at the model's representation layer. We convert complex corporate SOPs, SEC/FINRA regulations, and strict editorial rulebooks into machine-readable "Policy as Code," enforcing deterministic constraints and defensible audit trails without requiring expensive model retraining. The result is a step-function breakthrough in enterprise AI economics and capability. Our fundamental architecture allows organizations to run secure, self-hosted open-source models that mathematically match the reasoning and performance of frontier models. Benchmarks from our enterprise deployments demonstrate a 96.5% prevention of hallucinations, up to a 3.3× accuracy multiplier in complex domain-specific tasks, and an 80-90% reduction in human-in-the-loop manual review. Backed by an $8M seed round from Gradient Ventures (Google), General Catalyst, and Y Combinator, CTGT is currently deployed with Fortune 500 companies, including Tier-1 financial institutions and global media conglomerates, giving them the deterministic control necessary to deploy enterprise AI with zero margin for error. ## About the role #### About CTGT & The Mission Despite massive investment in commercial AI, organizations often find that demonstrated value is elusive, primarily due to the non-deterministic risk inherent to generative models. CTGT is the deterministic governance layer that enables the most important global institutions to deploy AI workflows with confidence. Born out of Stanford University research, we provide the control plane that makes it possible. A lightweight, model-agnostic system that enforces policy, prevents drift, and produces auditable decisions in real time. When benchmarked on HaluEval, the CTGT Policy Engine (paired with GPT-120B OSS) outperformed frontier models (Gemini 3 Pro Preview, Claude 4.5 Opus and 4.5 Sonnet) at drastically lower compute cost. While we sit on the edge of AI research, CTGT brings frontier intelligence into real-world environments. We apply cutting-edge theory directly in production to make large language models more reliable, controllable, and performant in practice. Our mission is to bring models to the level of performance and accountability required by the Fortune 500. By bridging the gap between LLM capabilities and domain-specific requirements, we unlock the true potential of generative AI to solve the most pressing problems in our world today. #### The Role This is not a side project internship. You will own a meaningful piece of work end to end, ship it to a real system, and see it used. You will sit close to the engineers building the Policy Engine and the platform around it, and you will be expected to form opinions, ask hard questions, and take problems further than they were handed to you. We are looking for someone whose strength is the fundamentals: someone who writes clean code, reasons carefully about correctness, and wants to understand the whole system rather than just the piece in front of them. #### #### What You Will Do - Build and ship features across the stack, from backend services to product surfaces - Write code that holds up under real load, with the correctness and clarity our systems require - Work closely with senior engineers and take ownership of a project from design through delivery - Dig into ambiguous problems and bring back a clear answer #### Who You Are - Pursuing a Bachelor's degree in Computer Science or a related technical field - Strong programming fundamentals and fluency in at least one general purpose language (Python and JavaScript are central to our stack) - Comfortable with Git and basic cloud workflows (AWS or GCP) - Able to explain technical ideas clearly to people with different backgrounds - Curious, self-directed, and able to make progress without constant scaffolding #### Logistics - Full-time, in person in San Francisco - 10 to 12 weeks between May/June and August/September 2027 - We sponsor US visas #### What We Offer - World-Class Backing: You will join a venture-backed company with institutional investors including Google's Gradient Ventures, General Catalyst, and Y Combinator. - Real Impact: You will work directly on the core systems that determine how models perform in the wild. Your work ships into real, high-stakes environments where governance, auditability, and performance are non-negotiable. - Autonomy & Trust: We operate with a high degree of trust. You are expected to form strong technical opinions and execute on them. --- Source: CTGT's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/ctgt-software-engineering-intern-summer-2027-0666738f-39dd-46e7-bfe8-2d2cc3cb96b1