AI Engineer (Remote, International)

Role overview

This opportunity is shared on behalf of a partner organization that handles the application review and all subsequent hiring steps. The opening is for an AI Engineer based in India, working remotely for an international team.

You will join a high-performing engineering group focused on designing and scaling AI systems built on large language models and live data. The role blends machine learning, distributed systems, and advertising technology, with a strong focus on scale, latency, and reliability. Your work will support both internal operations and customer-facing experiences through retrieval systems, chat-style interfaces, and decision-making automation.

In addition to building AI features, you will help strengthen the data foundations that power LLM-based products and other emerging AI workloads. The environment is collaborative and fast-moving, involving close work with engineers, analysts, and product teams. You will have room to test new frameworks, iterate quickly, and contribute to the long-term direction of generative AI platforms.

Key responsibilities

• Create, improve, and support AI components based on LLMs for internal tools and external user experiences.
• Build solutions that cover retrieval, embeddings, conversational systems, and automated decision workflows.
• Assess new models, tools, and architectural approaches as the generative AI space evolves.
• Enhance the supporting data infrastructure so LLM systems remain scalable and dependable.
• Work closely with engineering, analytics, and product partners to identify and deliver AI-driven use cases.
• Help shape the technical roadmap and future design of generative AI systems in a large-scale AdTech setting.
• Keep production systems running smoothly at high throughput, low latency, and with very large data volumes.

Required background

• Strong Python development experience, including familiarity with data libraries such as NumPy and Pandas.
• Good command of SQL and relational database concepts.
• Practical exposure to AI/ML systems such as LLM inference, embeddings, vector databases, or ranking models.
• Experience with distributed environments or container-based setups; Kubernetes knowledge is an advantage.
• Understanding of machine learning fundamentals and data-led problem solving.
• Strong analytical ability and the confidence to diagnose and resolve complex technical issues independently.
• Ownership-driven, proactive working style with accountability and initiative.
• Helpful extras include Java, time-series analysis, and experience with large-scale advertising or real-time systems.

What is offered

• Competitive pay benchmarked against international remote engineering roles.
• Chance to work on AI platforms handling billions of real-time events.
• Remote-first setup with a high degree of flexibility and autonomy.
• Exposure to advanced generative AI tools and rapid experimentation cycles.
• Open, collaborative engineering culture with direct access to technical leadership.
• Strong ownership over work that has production impact at massive scale.
• Opportunity to influence the future of LLM-powered systems in a fast-growing AdTech environment.

Application and hiring process

Applications are reviewed through an AI-assisted matching process designed to compare candidates fairly and quickly against the role’s core requirements. The resulting shortlist is then passed to the hiring company, which manages interviews, assessments, and final selection.

Data privacy and recruitment technology

By submitting an application, you agree that your personal information may be processed to assess your candidacy and shared with the hiring employer where appropriate. This processing is based on legitimate interest and pre-contractual steps under applicable data protection laws, including GDPR. You may request access, correction, deletion, or objection at any time.

Artificial intelligence tools may also be used to support parts of the recruitment workflow, such as resume screening, application review, response analysis, or identifying possible inconsistencies. These tools assist the recruitment team and do not replace human judgment; final hiring decisions are made by people. For more information about data handling, the applicant can contact the recruiting team.