
Eligibility Criteria
Bachelorβs degree in Computer Science, Engineering, Information Technology, or a related field; minimum 70% (or equivalent CGPA 8.0+) in the qualifying year; no backlogs; eligible for internship programs; strong programming background in Python; interest in AI agents, evaluation, alignment, or enterprise AI.

Job Description & Key Responsibilities
Lexsi Labs is a frontier AI laboratory dedicated to building aligned, interpretable, and safe AI systems for realβworld deployment. The organizationβs research portfolio spans agentic AI, alignment, interpretability, evaluation systems, enterprise AI, and foundational model research across structured, tabular, and proprietary data. Transparency, auditability, robustness, and controllability are treated as firstβclass constraints, ensuring that every system is not only powerful but also trustworthy.
The AI Agent Engineer Intern role invites candidates to tackle highβimpact agentic AI problems across applied, research, and product domains. Interns will not be confined to building small internal bots; instead, they will work on real agentic systems, evaluation infrastructure, enterprise use cases, research prototypes, and product tooling that can shape how AI agents are built, tested, aligned, and deployed. Depending on interests, interns may contribute to one or more of three tracks: Applied Agentic AI, Agent R&D and Evaluation, or Product and Tooling Agents.
Key responsibilities include:
1. Designing and prototyping enterprise workflow agents that reason over complex tasks.
2. Building evaluation frameworks to benchmark tool use, planning, and longβhorizon reasoning.
3. Developing harnesses for new agent architectures and studying failure modes.
4. Creating productβgrade tooling that improves researcher and engineer productivity.
5. Integrating LLMs with structured and proprietary data sources.
6. Collaborating with research, engineering, and product teams to iterate on prototypes.
7. Documenting findings, experiments, and design decisions.
8. Contributing to research papers, technical reports, or internal knowledge bases.
9. Maintaining clean, versionβcontrolled codebases.
10. Participating in code reviews and knowledge sharing sessions.
The technical stack revolves around Python, large language models, agent frameworks such as LangChain or custom harnesses, evaluation pipelines, cloud services (AWS/GCP), Git, Docker, and data connectors for enterprise systems. Strong programming skills, a passion for agents, and a willingness to tackle ambiguous problems are essential.
Growth opportunities are abundant: interns can progress to research engineers, product engineers, or research scientists, publish papers, contribute to openβsource projects, and lead crossβfunctional initiatives. The fastβmoving, researchβdriven environment encourages ownership, rapid prototyping, and the translation of ideas into productionβgrade components.
Why join Lexsi Labs? The lab offers a chance to work at the frontier of agentic AI, collaborate with worldβclass researchers, and build systems that have tangible realβworld impact. Flexible remote work, partβtime scheduling, and a culture that values substance over polish make this internship an ideal launchpad for aspiring AI professionals.