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Wise
Wise

Focused on global money transfers.

Senior Software Engineer - Contact Automation - AI

직무엔지니어링
경력시니어급
위치Budapest
근무오피스 출근
고용정규직
게시1주 전
지원하기

About the Role

As a Senior Software Engineer in the Contact Automation team, you will play a pivotal role in shaping the future of customer support at Wise. You'll be a key technical leader in an autonomous team, driving the vision and end-to-end solutions for the Wise Assistant. This is a high-impact role where you'll tackle complex engineering challenges to automate real customer issues, significantly improving their experience and our operational efficiency.

How We Work

  • Agile & Collaborative: We operate in an agile fashion, fostering close collaboration between engineers, product managers, content designers, analysts, and data scientists.

  • Cross-Functional Teams: You'll work alongside talented individuals to design, build, and iterate on solutions that deliver tangible customer value.

  • International Presence: Our team is distributed across our Budapest, New York and London offices, offering a diverse and dynamic working environment.

What You'll Be Working On

  • Lead the design, development, and deployment of scalable, resilient, and high-performance components for the Wise Assistant. This includes our core Java microservice consuming Kafka messages, as well as contributing to our Typescript and Python codebases.

  • Take ownership of our intent detection systems, contact processing pipelines, and the routing logic that connects customers to various automation solutions (templates, RAG, LLM workflows, AI agents, Vendor solutions)

  • Innovate with AI: Design and implement solutions leveraging foundational LLM models (AWS Bedrock) to resolve customer queries effectively

  • Integrate & Orchestrate: Lead and manage the technical integration with third-party AI Agent vendors, ensuring seamless and robust connectivity.

  • Scale & Optimize: Continuously improve the performance, reliability, and scalability of our automation platform to handle growing volumes and complexity.

  • Collaborate for Impact: Work closely with content designers to implement and refine automated conversational flows, ensuring a high-quality user experience.

  • Mentor: Provide technical guidance and mentorship to other engineers, fostering a culture of engineering excellence and continuous learning.

What You Need We are fully aware that it is uncommon for a candidate to have all skills required, and we fully support everyone in learning new skills with us. If you possess many of the skills listed below and are eager to learn and grow, we strongly encourage you to apply!

  • AI Engineering Experience: Experience in applying AI/ML concepts, particularly LLMs, to solve real-world problems in production environments. (The Rise of the AI Engineer)

  • Pragmatic & Impact-Oriented: You recognize that achieving significant customer impact sometimes requires dedicated effort on foundational or less technically novel tasks, and you approach all work with the same commitment to quality and solving the underlying customer problem.

  • Excellent communication and interpersonal skills, with a talent for collaborating effectively with

  • Deep experience in designing, building, and maintaining microservices. Strong proficiency in Java is essential, particularly in an event-driven architecture (e.g., Kafka).

  • Solid experience with both relational and non-relational databases, including query optimization and schema design.

  • Proven ability in designing, deploying, and maintaining clean, well-documented RESTful APIs.

  • diverse teams and bringing people together to solve challenging problems.

  • A firm believer in and practitioner of best coding practices, including thorough code reviews, automated testing, and a culture of open feedback.

  • Experience building and fine-tuning production-grade RAG (Retrieval Augmented Generation) systems.

  • Experience with designing and implementing evaluation frameworks (evals) for LLM-based solutions.

  • Hands-on experience with AWS Bedrock and its enterprise features for deploying and managing LLMs.

  • Familiarity with Agentic workflows, AI Agent solutions, and multi-agent systems.

  • Prior experience in automating customer support and servicing operations

For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

More about

[our mission](https: //wise.jobs/our-mission) and

[what we offer](https: //wise.jobs/what-we-offer).

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Wise 소개

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1-50

직원 수

Bradford

본사 위치

$8.0B

기업 가치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

3.2

보상

4.0

문화

4.1

커리어

3.5

경영진

3.7

72%

지인 추천률

장점

Flexible work hours and remote options

Supportive and approachable management

Collaborative environment and teamwork

단점

High workload and unpredictable demands

Communication issues and lack of direction

Stressful and overwhelming work environment

연봉 정보

117개 데이터

Mid/L4

Senior/L5

Mid/L4 · Product Application Analyst

1개 리포트

$87,400

총 연봉

기본급

$76,000

주식

-

보너스

-

$87,400

$87,400

면접 후기

후기 4개

난이도

2.3

/ 5

소요 기간

14-28주

합격률

50%

경험

긍정 25%

보통 25%

부정 50%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Interview Round

4

Technical/Role-specific Interview

5

Final Interview

6

Offer Decision

자주 나오는 질문

Technical Knowledge

Past Experience

Behavioral/STAR

Role-specific Skills

Problem Solving