Find opportunities to take part in real projects while learning from mentors with extensive industry experiences
In Partnership With
The Opportunity
Work alongside Infinite Analytics' engineering and product teams to help develop the next generation of SherlockAI's intelligent agents, conversational search capabilities, and underlying data systems.
This fellowship offers an opportunity to contribute directly to a live AI product, participating in the process of designing, building, testing, evaluating, and improving technology used to address real business challenges.
Participants will gain exposure to the complete product development lifecycle, including early-stage ideation, architecture discussions, technical implementation, code reviews, quality assurance, and deployment preparation.
Importantly, this is not limited to completing predefined technical assignments. Fellows will have opportunities to participate in zero-to-one development, helping transform new concepts and proposed capabilities into working solutions.
What You'll Work On
AI agent development: Help design, build, test, and improve AI agents that interpret complex business questions and generate actionable insights using SherlockAI's data and tools.
Product development: Contribute to the development of Sherlock Search and other platform capabilities, including new features, workflows, and internal tools.
Technical strategy: Participate in engineering discussions and brainstorming sessions around product architecture, agent behavior, technical challenges, and potential solutions.
Code development and review: Write, review, debug, and improve code alongside experienced engineers, receiving feedback on technical approaches, coding standards, and implementation decisions.
AI evaluations and quality assurance: Work with engineering and QA teams to develop test cases, evaluate agent performance, investigate inaccuracies, and improve the reliability and consistency of outputs.
Data engineering: Gain experience working with complex datasets, SQL queries, data pipelines, and the systems that support SherlockAI's intelligence capabilities.
Zero-to-one execution: Take ownership of defined technical initiatives, helping move projects from initial ideas through prototyping, testing, iteration, and internal presentations.
Cross-functional collaboration: Coordinate with product, data, strategy, and commercial teams to understand user requirements and translate real business needs into technical solutions.
Technical communication: Present findings, demonstrate completed work, explain technical trade-offs, and communicate recommendations to the wider team.
What You'll Gain
Participants will develop practical experience working with modern AI systems, including LLM APIs, agent workflows, tool integrations, evaluation frameworks, and large-scale data infrastructure.
They will learn how experienced engineers approach system design, technical decision-making, code quality, debugging, and product development.
Fellows will also gain an understanding of the commercial side of AI: how customer challenges influence technical priorities, how product performance is measured, and how sophisticated technology is translated into valuable business applications.
Interested participants will have opportunities to shadow other functions, attend selected strategy and product meetings, and engage with the broader team to understand how engineering fits into the organization's overall growth.
The objective is to give fellows the responsibility to build and own meaningful components of a real AI product, supported by experienced professionals who can help accelerate their technical and professional development.
First-Month Focus
Participants will begin by learning SherlockAI's architecture, business applications, and existing agent capabilities.
Initial activities will include supporting quality assurance, understanding current engineering workflows, setting up development environments, participating in team discussions, and completing an introductory technical assignment.
As familiarity grows, fellows will transition into more substantial development work, with opportunities to take ownership of defined projects.
Who Might Be a Fit
Students or early-career candidates studying computer science, data science, artificial intelligence, machine learning, data engineering, or related fields.
Familiarity with Python, SQL, and Git is valuable, along with exposure to LLM APIs, AI agents, chatbots, retrieval systems, or similar technologies through academic, professional, or personal projects.
Experience with Trino, Spark, geospatial data, or large-scale data systems is a plus.
Above all, we value curiosity, strong problem-solving abilities, a willingness to learn, and the initiative to turn ideas into working solutions.
Your Journey Starts Here
Apply to put the skills you've learned to the test, and gain practical experience to kickstart your career
