AI Tech Lead

Mastercard is hiring an AI Tech Lead. Level rates it ; you can apply on Level.

AI in this role

openailangchainlanggraphbedrock

ragai-agentsai-evaluation

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

AI Tech Lead

Job Description Summary
We are seeking an experienced AI Tech Lead to lead the design and development of scalable backend systems and production-grade AI applications.
This is a hands-on technical leadership role combining deep Python/backend engineering expertise with proven experience building and deploying GenAI applications and AI agents used by end users in production.

You will shape the architecture of our AI-powered products, build scalable backend services and agentic AI solutions, and lead engineers in delivering reliable, high-performance systems at scale.

Key Responsibilities

Backend & Technical Leadership

Lead the architecture and development of scalable Python backend systems, services, and APIs.
Design distributed systems and microservices with a focus on performance, scalability, reliability, and security.
Remain hands-on with architecture, coding, code reviews, and complex technical problem-solving.
Define engineering best practices across backend and AI development.

AI & Agentic Engineering

Design and build production-grade GenAI applications and AI agents used by end users.
Build agentic workflows including LLM orchestration, tool calling, context management, memory, and service integrations.
Integrate LLMs and other AI models into scalable production applications.
Build solutions using technologies such as Amazon Bedrock, OpenAI, LangChain, and LangGraph.
Implement LLM evaluation, tracing, monitoring, and observability.
Optimize AI solutions for quality, latency, reliability, scalability, and cost.
Take AI capabilities from experimentation and POC through to production and end-user adoption.

Team Leadership & Delivery

Lead, mentor, and provide technical guidance to backend and/or full-stack engineers.
Partner with Product, AI/Data, DevOps, and Architecture teams to define and deliver technical solutions.
Drive complex projects from design through deployment and production monitoring.
Foster a strong engineering culture focused on ownership, innovation, and quality.

Required Qualifications

8+ years of software engineering experience with strong backend development expertise.
Strong hands-on Python experience, particularly building production backend services and applications.
2+ years in a technical leadership or Tech Lead role.
Proven experience designing large-scale distributed systems and microservices.
Hands-on experience building and deploying GenAI applications and AI agents in production.
Experience taking LLM/agentic solutions beyond POC into applications used by end users.
Experience with LLMs, agent orchestration, tool calling, context management, and AI/backend integrations.
Experience with Amazon Bedrock, OpenAI, LangChain, LangGraph, or similar technologies.
Understanding of production AI considerations including evaluation, observability, latency, reliability, scalability, and cost.
Experience with cloud platforms, preferably AWS, as well as Docker and Kubernetes.
Strong system design and problem-solving skills.

Preferred Qualifications

Experience with multi-step or multi-agent AI systems.
Experience with LLM evaluation and observability tools such as Langfuse.
Experience with RAG, retrieval systems, embeddings, or vector search.
Experience with real-time data technologies such as Kafka, Spark, or Flink.
Experience with Node.js alongside Python.

Tech Stack

Backend: Python, Node.js
AI: Amazon Bedrock, OpenAI, LangChain, LangGraph, Langfuse
Data: PostgreSQL, Redis, DynamoDB, Snowflake
Infrastructure: AWS/GCP, Docker, Kubernetes
Streaming: Kafka
CI/CD: GitHub Actions

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

Abide by Mastercard’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

How we rate this

AI Tech Lead at Mastercard rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

AI Tech Lead is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Ramat-Gan, Israel.
The job was posted on June 17, 2026.
Seniority: lead.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsAI EvaluationOpenAILangChainLangGraphBedrock

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you decide that one model's output is better than another's for a given task?
What's a project where you used OpenAI hands-on?
Walk me through how you've used LangChain in your day-to-day work.

Adapt your resume

List these exact terms on your resume: RAG, AI agents, AI Evaluation, OpenAI, and LangChain. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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