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Conversational AI Engineer

Google

Conversational AI Engineer

Google

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Top Tier compensation with equity

Parental leave program

Health, dental, and vision coverage

Flexible PTO policy

Annual team offsites

Wellness benefits

Required Skills

Python

Airflow

Apache Spark

About the job

As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships.

You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

  • Build virtual agent solutions on Google’s core conversational AI platforms such as Dialogflow.

  • Work with customer technical leads, client executives, and partners to scope, manage and deliver successful implementations of contact center Artificial Intelligence (AI) solutions.

  • Interact with partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for successful client outcomes. Advocate for customer needs in order to overcome adoption blockers and drive new feature development based on your field experience.

  • Propose solution architectures and manage the deployment of cloud based virtual agent solutions according to customer requirements and implementation best practices.

  • Travel 30% of the time for client engagements as required.

Minimum qualifications

  • Bachelor's degree in Computer Science or equivalent practical experience.

  • 3 years of experience in computational linguistics or engineering.

  • Experience in working with customers, executives, and technical leads.

  • Experience in building chatbots or voicebots.

Preferred qualifications

  • Experience with launching chatbot or voicebot applications.

  • Experience building cloud-based Conversational AI solutions.

  • Experience with natural language processing and related concepts.

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

63,375 data points

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0 reports

$176,704

total / year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview Experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer Rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview Process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense