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职位Hearst

Senior Engineer, Generative AI

Hearst

Senior Engineer, Generative AI

Hearst

New York, NY, United States, US

·

On-site

·

Full-time

·

2mo ago

必备技能

Python

JavaScript

React

Docker

Project Management

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst's Chief Product & AI Strategist. This role sits at the intersection of software engineering and artificial intelligence, focusing on building and deploying cutting-edge AI applications that drive business value.

Key Responsibilities:

Design and develop Generative AI applications and features using modern LLM APIs and open-source models
Create and optimize multi-agent systems using frameworks like Lang Chain and advanced RAG architectures
Build robust systems that combine traditional software engineering with Generative AI capabilities
Implement and maintain AI pipelines using vector databases and retrieval systems
Develop evaluation frameworks to assess Generative AI application performance and reliability
Collaborate with product teams to identify and implement AI-driven solutions

Requirements:

5+ years of software development experience with strong proficiency in Python and JavaScript
Familiarity with containerized development (e.g. Docker) and deployment
Exposure to one or more modern JS frameworks like React/Next/Node
Experience with modern Generative AI development frameworks and tools (Lang Chain, Vector DBs)
Demonstrated ability to work with LLM APIs (GPT-4, Claude, etc.)
Familiarity the use of agentic software development tools like Cline and Cursor
Strong understanding of prompt engineering and LLM capabilities
A commitment to automated testing and software development best practices
Strong problem solving and project management skills and ability to work with ambiguous requirements
Excellent communication skills to explain AI capabilities and limitations to stakeholders

Advanced Skills (Nice to Have)

Experience with complex RAG architectures incorporating graph databases
Familiarity with agent orchestration frameworks like Lang Graph or CrewAI
Experience with LLM evaluation and monitoring tools like Lang Smith
Knowledge of advanced retrieval techniques beyond semantic search

In accordance with applicable law, Hearst is required to include a reasonable estimate of the compensation for this role if hired in New York City. The reasonable estimate, if hired in New York City, is $175,000 - $200,000. Please note this information is specific to those hired in New York City. If this role is open to candidates outside of New York City, the salary range would be aligned to that specific location. A final decision on the successful candidate’s starting salary will be based on a number of permissible, non-discriminatory factors, including but not limited to skills and experience, training, certifications, and education. Hearst provides a competitive benefits package, including medical, dental, vision, disability and life insurance, 401(k), paid holidays and paid time off, employee assistance programs, and more.

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关于Hearst

Hearst

Hearst

Public

Hearst Corporation, Hearst Holdings Inc. and Hearst Communications Inc. is an American multinational mass media and business information conglomerate owned by the Hearst family and based in Hearst Tower in Midtown Manhattan in New York City.

10,001+

员工数

New York

总部位置

评价

3.7

10条评价

工作生活平衡

3.2

薪酬

3.5

企业文化

4.1

职业发展

3.4

管理层

3.1

68%

推荐给朋友

优点

Great team culture and colleagues

Good growth and learning opportunities

Excellent health benefits and vacation time

缺点

Heavy workload and overtime expectations

Management issues and communication problems

Salary and compensation concerns

薪资范围

30个数据点

Junior/L3

L4

Mid/L4

Principal/L7

Staff/L6

Junior/L3 · Product Designer

0份报告

$122,000

年薪总额

基本工资

-

股票

-

奖金

-

$103,700

$140,300

面试经验

45次面试

难度

3.1

/ 5

时长

14-28周

录用率

38%

体验

正面 61%

中性 20%

负面 19%

面试流程

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

常见问题

Technical skills

Past experience

Team collaboration

Problem solving