What You’ll Do

• Build and enhance AI agents and agentic workflows using Python, Go language, LLMs, and modern AI frameworks.
• Develop backend services, APIs, and integrations that support production AI applications.
• Work with Agent SDKs and Model Context Protocol (MCP) to connect agents with tools, data, and services.
• Help build AI guardrails, controls, monitoring, tracing, and observability to make AI applications safer and more reliable.
• Partner with senior AI and software engineers to turn prototypes into scalable, production-ready applications.
• Build and test integrations with GCP/AWS, APIs, databases, and containerized services.
• Experiment with new LLMs, agent frameworks, AI developer tools, and automation technologies.
• Participate in code reviews, testing, debugging, deployment, and technical design discussions.
• Learn how production AI systems are secured, monitored, evaluated, and governed.
• Build, deploy, and operate containerized AI services and agent workloads on Kubernetes in cloud environments such as GCP/AWS.

What We’re Looking For

• Recent graduate or 0–2 years of software engineering experience.
• Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, Data Science, Computer Engineering, or similar technical discipline.
• Strong programming fundamentals with Python.
• Understanding of APIs, backend development, databases, and basic software architecture.
• Hands-on exposure to LLMs, generative AI, AI agents, or agentic workflows through internships, university projects, research, hackathons, or personal projects.
• Familiarity with at least one AI/LLM framework or SDK such as OpenAI SDK, Anthropic, LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Basic understanding of cloud technologies; GCP/AWS experience is a plus.
• Interest in learning MCP, AI security, guardrails, observability, and agent control systems.
• Exposure to Kubernetes, Docker, and cloud-native application deployment
• Strong problem-solving skills and curiosity about how AI systems work under the hood.
• Comfortable learning quickly and working closely with experienced engineers in a fast-moving environment.

Preferred Qualifications

• Internship, research, or project experience building an AI agent, RAG application, chatbot, copilot, or AI automation.
• Experience with Git, Docker, Linux, REST APIs, SQL/NoSQL, or AWS.
• Exposure to MCP or Agent SDKs.
• Familiarity with prompt engineering, embeddings, vector databases, RAG, or tool/function calling.
• Exposure to AI evaluation, hallucination reduction, security guardrails, or LLM observability.
• Coursework or projects involving machine learning, distributed systems, cloud computing, cybersecurity, or backend engineering.

About Tilda Research, Inc.

About Tilda

Tilda Research is reimagining how clinical trials are run by bringing AI-native tools and AI teammates into clinical research operations. Our technology works alongside sponsor, CRO, and research teams to simplify study management, improve data quality, support real-time oversight, and help accelerate trial timelines.

We are building the future of clinical trial execution: one where research teams can spend less time on administrative bottlenecks and more time focused on patients, sites, and the work that moves new treatments forward. Tilda’s mission is rooted in the belief that clinical research should be faster, more efficient, more scalable, and more accessible — without losing the human judgment and care that patients and research teams deserve.

At Tilda, we are a team of builders, operators, researchers, and problem-solvers working at the intersection of healthcare, technology, and AI. We move quickly, think deeply, and care about building products and systems that create meaningful impact in the clinical research industry.