Solutions Architect

Reposted 8 Days Ago
Be an Early Applicant
4 Locations
In-Office
195K-269K Annually
Mid level
Machine Learning
The Role
Join Tecton as a Solutions Architect to drive technical decisions, enable customer adoption of AI/ML solutions, and provide expertise in data systems.
Summary Generated by Built In

At Tecton, we solve the complex data problems in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions, abstracting away the complex engineering to speed up innovation.

Tecton’s founders developed the first Feature Store when they created Uber’s Michelangelo ML platform, and we’re now bringing those same capabilities to every organization in the world.

Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.

Solution Architects at Tecton are trusted advisors who drive both new business and long-term customer success. You’ll work with Account Executives to lead evaluations, guide platform adoption, and help customers scale their use of Tecton with confidence.

This role goes beyond demos—it’s about storytelling and solutioning. You’ll help customers envision what’s possible, design the right architectures, solve complex challenges, and serve as a trusted advisor throughout their journey.

Tecton is on a mission to make ML and AI production-ready for every enterprise with the most trusted feature platform for delivering production-grade features from any data—batch, or streaming.

As a Solution Architect, you’ll join a world-class team tackling complex data challenges, working with some of the most innovative companies, and shaping how the next generation of intelligent applications is built. If you’re passionate about solving impactful problems and thriving in a fast-moving, collaborative environment—you’ll fit right in.

Responsibilities
  • Understand customer needs & win technical decisions: Assess customer architectures and ML ecosystems, lead discovery and evaluations, and demonstrate Tecton’s value to drive confident purchase decisions.

  • Enable adoption & scale: Guide customers through onboarding, expansion, and best practices to grow platform maturity and operational excellence.

  • Advance customer success: Monitor adoption trends, optimize usage, and identify opportunities for new use cases and expansion.

  • Amplify expertise: Deliver thought leadership through talks, workshops, and enablement while building reusable demos, playbooks, and reference architectures.

  • Champion the customer voice: Capture and share customer feedback to influence Tecton’s roadmap.

  • Represent Tecton externally: Engage with the broader data and ML ecosystem at meetups, events, and technical communities.

Qualifications
  • Technical Depth in Data & ML Ecosystems: Hands-on knowledge of ML/AI workflows, data pipelines, streaming and batch systems (e.g., Spark, Flink, Kafka, Snowflake), and cloud-native architectures (AWS, GCP, Azure).

  • Pre-Sales Account Management Expertise: Proven success winning technical evaluations and driving adoption within existing customers..

  • Solution Storytelling: Translate complex capabilities into clear business value.

  • Communication & Presence: Confident presenting to engineers, architects, and executives.

  • Collaboration: Partner effectively across teams and share reusable best practices.

  • Adaptability: Thrive in fast-changing, complex technical environments.

  • Customer Focus: Build trust quickly and prioritize customer success.

The estimated US salary range for this position is $195,000 - $269,000 annually for employees based within California & New York. This role is eligible to participate in Tecton’s Commission Plan and the estimated total on-target annual earnings is $169,000 - 266,000 OTE we offer competitive equity & comprehensive benefits such as medical, dental, vision, life, 401(K), flexible paid time off, 10 paid holidays each calendar year, sick time, leave of absence as per the FMLA and other relevant leave laws. Individual compensation packages are based on multiple factors such as location, level, role scope, and complexity, as well as additional job-related factors such as skills, experience, and expertise.

Tecton is a remote-friendly company that employs a hybrid working policy for employees based in the SF, NY, and Seattle areas. We believe that working in-person helps us stay connected, collaborate faster, and promote a strong culture while still providing the flexibility of working from home. We expect SF & NY employees to be in the office at least two designated days per week, and those in the Seattle area at least two designated days per month.

Tecton values diversity and is an equal opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics.  If you would like to request any accommodations from the application through to the interview, please contact us at [email protected].

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Top Skills

AI
AWS
Azure
Batch Systems
Data Pipelines
Flink
GCP
Kafka
Machine Learning
Snowflake
Spark
Streaming Systems
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The Company
HQ: San Francisco, CA
88 Employees
Year Founded: 2019

What We Do

Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company.

Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes.

But ML models will only ever be as good as the data that is fed to them. Today, it’s incredibly hard to build and manage ML data. Most companies don’t have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production.

We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.

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