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Solutions Architect, Applied AI

LangChain

Solutions Architect, Applied AI

LangChain

San Francisco, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$170,000 - $200,000

Benefits & Perks

Generous paid time off and holidays

Parental leave

Competitive salary and equity package

Comprehensive health, dental, and vision insurance

Parental Leave

Equity

Healthcare

Required Skills

PostgreSQL

TypeScript

Node.js

ABOUT THE ROLE:

We are hiring our first Applied AI Solutions Architect to help define how partners and enterprises adopt agentic AI using Lang Chain, Lang Graph, and Lang Smith.

This is a hands on technical role working closely with cloud providers, system integrators, and technology partners to build integrations, reference architectures, and production ready demos. You will work at the intersection of engineering, product, partnerships, and GTM, translating partner and customer needs into scalable technical solutions.

WHAT YOU’LL DO:

  • Partner with cloud providers, technology ISV and startups, and system integrators to design and build agentic AI solutions.

  • Create production ready solutions, sample repositories, and reference architectures using Lang Chain, Lang Graph, and Lang Smith.

  • Collaborate closely with product and engineering teams to support partner integrations and solution design.

  • Enable partners through technical workshops, solution walkthroughs, and hands on collaboration.

  • Gather partner and customer feedback and translate it into actionable insights for product and integration roadmaps.

HOW TO BE SUCCESSFUL IN THE ROLE:

  • 5 or more years in technical, customer or partner facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, Dev Rel, or Applied AI Engineer.

  • Strong Python skills and experience building and deploying solutions on cloud platforms, with AWS preferred.

  • Experience working with LLMs, RAG, agents, orchestration frameworks, or ML infrastructure.

  • Ability to collaborate effectively with external partners on complex technical projects.

  • Strong communication skills and comfort explaining technical concepts to both technical and non technical audiences.

  • Start up DNA - the ability to thrive in a fast paced, scaling environment.

  • Experience taking generative AI or agent based systems from prototype to production, preferred.

  • Hands on experience with Lang Chain, Lang Graph, Lang Smith, or similar agent frameworks, would be a big bonus.

  • Background in cloud native architectures including serverless, containerized, or VPC based deployments, preferred.

  • Prior open source contributions or technical content creation, would be a bonus.

COMPENSATION AND BENEFITS:

We offer competitive compensation including base salary, equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Compensation varies based on role, level, and location.

Annual salary range: $170,000 to $200,000 USD

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About LangChain

LangChain

LangChain

Series B

A platform that provides open-source frameworks and tools for engineering and deploying language model agents.

51-200

Employees

San Francisco

Headquarters

$200M

Valuation

Reviews

3.4

3 reviews

Work Life Balance

2.5

Compensation

3.0

Culture

2.8

Career

3.2

Management

2.3

35%

Recommend to a Friend

Pros

Working with cutting-edge AI technologies like LangChain and RAG

Hands-on experience building end-to-end AI projects

Exposure to modern applied AI development

Cons

Uncertainty about long-term career prospects and employability

Projects rarely make it to production use

Lack of senior developer mentorship and guidance

Salary Ranges

9 data points

Mid/L4

Mid/L4 · Product Designer

1 reports

$178,619

total / year

Base

$155,147

Stock

-

Bonus

-

$178,619

$178,619

Interview Experience

10 interviews

Difficulty

2.7

/ 5

Duration

14-28 weeks

Offer Rate

60%

Experience

Positive 50%

Neutral 40%

Negative 10%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Take-home

4

Technical Interview

5

Virtual Onsite/Final Round

6

Offer

Common Questions

System Design

Machine Learning/AI Knowledge

Coding/Algorithm

Technical Architecture

Behavioral/STAR