Lexsi Labs is hiring AI Agent Engineer Interns for candidates who want hands-on exposure to Agentic AI, LLMs, AI evaluation, enterprise AI, research, and intelligent tooling. This opportunity is particularly relevant for B.E./B.Tech/M.E./M.Tech students and recent graduates who want to build practical AI systems rather than work only on conventional software projects.
π Job Details
β’ π’ Company: Lexsi Labs
β’ πΌ Role: AI Agent Engineer Intern
β’ π Qualification: B.E./B.Tech/M.E./M.Tech
β’ π¨βπ Eligible Passing Years: 2025, 2026, 2027
β’ π Location: Remote / Work From Home
β’ π° Expected Salary: βΉ40,000ββΉ60,000 per month
β’ π§ Domain: Applied AI, Agentic AI, AI Research & Product Engineering
β’ β±οΈ Employment: Part-Time Internship
β’ π Job Location Listed By Company: Mumbai Metropolitan Region / Remote
π’ About Lexsi Labs
Lexsi Labs is a frontier AI research and engineering organization focused on building AI systems that are aligned, interpretable, robust and suitable for real-world deployment. Its work spans agentic AI, alignment, interpretability, evaluation systems, enterprise AI and foundational models. The company describes its mission around building the foundations for Safe Superintelligence and turning frontier AI research into trusted autonomous systems.
For this internship, the focus moves beyond simple chatbot development. Interns can work on agent architectures, evaluation frameworks, planning and memory systems, enterprise workflows, research prototypes and product tooling.
π Why This Role Is Good for Interns?
This internship can be valuable for students who want to build a profile around AI Engineering rather than only traditional software development. You may work across three major directions:
β’ π€ Applied Agentic AI: Build agents capable of reasoning through workflows, using tools and data systems, executing multiple steps and evaluating outcomes.
β’ π¬ Agent R&D & Evaluation: Work on agent harnesses, benchmarks, failure analysis, evaluation frameworks, long-horizon reasoning, alignment and interpretability.
β’ π οΈ Product & Tooling Agents: Develop AI-powered tools that improve workflows for researchers, engineers and enterprise users.
π§ Skills Required
Candidates should focus on a combination of software engineering + AI fundamentals + experimentation:
β’ π Strong Python programming and clean coding practices
β’ π€ Understanding of LLMs and modern AI systems
β’ π Knowledge of AI agents, tool calling and multi-step workflows
⒠𧩠Understanding of planning, memory and agent architectures
β’ π AI evaluation, benchmarking and failure analysis
β’ π§ͺ Ability to design experiments and interpret results
β’ π Ability to read technical papers and convert ideas into prototypes
β’ βοΈ Familiarity with APIs, backend development and data systems
β’ π Git/GitHub and collaborative development
β’ π Strong technical documentation and communication
Bonus skills include LangChain/LangGraph or similar agent frameworks, RAG, vector databases, open-source contributions, research projects, enterprise data and AI safety/interpretability.
π― Preparation Tips
β’ Build one meaningful AI agent project that can call tools, maintain context, execute multiple steps and handle failures.
β’ Be ready to explain your complete architecture: LLM β planner β tools β memory/state β evaluator β final response.
β’ Learn how RAG, function/tool calling, agent loops, planning and memory work.
β’ Practice evaluating an AI agent using measurable metrics instead of simply checking whether its answer βlooks good.β
β’ Prepare examples of hallucination, tool failure, incorrect planning and infinite/long-running agent loops, along with ways to detect and handle them.
β’ Read at least a few recent papers or technical articles related to agents, evaluation, alignment or interpretability and be prepared to discuss one idea.
β’ Practice open-ended problem solving because the JD specifically emphasizes ambiguity, independent direction and turning ideas into working prototypes.
π Expected Interview Rounds at Lexsi Labs
β’ π Round 1 β Intro/Screening: Education, projects, AI interests, availability and motivation for joining Lexsi.
β’ π§ Round 2 β Technical AI Discussion: Python, LLMs, agents, RAG, tool calling, evaluation and AI-system fundamentals.
β’ π» Round 3 β Project/Problem-Solving Discussion: Explain an AI project, architecture, design decisions, failures and improvements; a practical task may also be possible.
β’ π€ Round 4 β Final Fit/Research Discussion: Ownership, curiosity, communication, ability to work independently and preferred AI track.
π° Salary Range
The hiring information provided for this opening states an expected compensation of βΉ40,000ββΉ60,000 per month. The accompanying compensation graphic also shows a broader internship range of βΉ20,000ββΉ60,000 per month, indicating that compensation can vary by experience, profile and internship arrangement. Candidates should confirm the final stipend directly during the selection process.
π Resume Tips
Your resume should make your AI-building ability visible within the first few seconds:
β’ Mention Python, LLMs, Agentic AI, RAG, APIs and relevant frameworks prominently.
β’ Add 1β3 strong AI projects rather than listing many basic academic projects.
β’ For every project, explain what the agent actually did and which tools/data it used.
β’ Include measurable outcomes such as evaluation accuracy, latency improvement, number of tools integrated or test cases evaluated.
β’ Add GitHub/open-source work if available.
β’ Mention research papers, technical blogs, hackathons or AI competitions where relevant.
β’ Highlight independent experimentation and projects where you solved an unclear problem without step-by-step instructions.
π How to Apply
π Application Link: Click Here
Interested candidates should apply for the AI Agent Engineer Intern opening through the Lexsi Labs application process. Keep your resume focused on AI/engineering projects and be prepared to discuss one project deeply from architecture to limitations and future improvements.
π₯ If you are a 2025, 2026 or 2027 B.E./B.Tech/M.E./M.Tech candidate passionate about Agentic AI, this internship can give you exposure to real AI engineering, evaluation and research-oriented development.
