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Senior Engineer, Generative AI

Hearst

Senior Engineer, Generative AI

Hearst

New York, NY, United States, US

·

On-site

·

Full-time

·

1mo ago

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 LangChain 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 (LangChain, 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 LangGraph or CrewAI
  • Experience with LLM evaluation and monitoring tools like LangSmith
  • 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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About 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+

Employees

New York

Headquarters

Reviews

3.7

16 reviews

Work Life Balance

3.5

Compensation

3.9

Culture

3.8

Career

3.8

Management

3.4

73%

Recommend to a Friend

Pros

Good work-life balance and flexible environment

Interesting projects and challenges

Competitive compensation and benefits

Cons

Some organizational bureaucracy

Room for improvement in processes

Work-life balance varies by team

Salary Ranges

31 data points

Mid/L4

Director

Mid/L4 · Senior Product Analyst, E-Commerce

1 reports

$221,000

total / year

Base

$170,000

Stock

-

Bonus

-

$221,000

$221,000

Interview Experience

45 interviews

Difficulty

3.1

/ 5

Duration

14-28 weeks

Offer Rate

38%

Experience

Positive 61%

Neutral 20%

Negative 19%

Interview Process

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

Common Questions

Technical skills

Past experience

Team collaboration

Problem solving