Bright Data is hiring a Solutions Engineer to support our micro business and AI startup segment. This role combines technical discovery, onboarding, code-level solutioning and self-service content creation. You will work closely with AI-native startups in our startup program while also helping smaller customers get set up quickly, adopt successfully and grow over time.
Why join Bright Data
This role blends solutions engineering, AI advisory, onboarding and scaled enablement in a way that is highly relevant to Bright Data’s startup and micro business motion. It is a strong fit for someone who enjoys solving customer problems directly while also building reusable systems, content and technical assets that support a more product-led experience.
*This is a hybrid position based in San Francisco or New York City*
What you'll do
Partner with AI startup accounts and run insight-led discovery to understand their product, model strategy, data needs and likely future requirements.
Act as a technical advisor by mapping use cases across LLMs, RAG, agent workflows and data pipelines to Bright Data solutions.
Nurture accounts technically over time by anticipating onboarding gaps, configuration needs, expansion triggers and new use cases before the customer asks.
Lead technical workshops, webinars, perform code reviews, troubleshoot integrations and build sample implementations, scripts and reference architectures in Python and/or JavaScript.
Support customers using MCP, agent skills, hooks and modern agent frameworks and provide technical guidance on how to integrate with Bright Data solutions.
Lead onboarding and configuration activities including authentication, setup, workflow design and faster time-to-first-value for both technical and non-technical customers.
Create technical documentation, implementation guides, troubleshooting runbooks and short video tutorials that promote self-service adoption.
Partner with Sales, Product, Engineering and Field Marketing to convert customer needs into repeatable solutions and expansion opportunities.
Requirements
3+ years in a customer-facing technical role such as Solutions Engineer, Solutions Architect, Implementation Engineer, Developer Advocate or Technical CSM.
Strong AI fluency, including practical understanding of LLMs, RAG, model behavior, VLMs, VLAs and agentic AI workflows.
Ability to read, write and review production-quality Python and/or JavaScript code for APIs, automations and data workflows.
Hands-on experience with MCP, agent skills, tool calling and familiarity with at least one agent frameworks such as LangGraph, CrewAI, AutoGen, or similar systems.
Experience onboarding customers and translating technical concepts into clear, practical guidance for both technical and non-technical users.
Proven ability to produce strong written documentation and video-based enablement content that drives self-service adoption.
Strong ownership, startup comfort and the ability to balance direct customer support with building scalable assets for future customers.