Software Engineer - Back End

Reposted 16 Days Ago
2 Locations
Hybrid
300K-300K Annually
Mid level
Artificial Intelligence • Software
The Role
As an AI Platform Engineer, design and optimize the AI-native platform, develop scalable infrastructure, and collaborate with teams to solve complex AI deployment challenges.
Summary Generated by Built In
About Distyl AI

Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.
We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.

What We Are Looking For

As a Software Engineer Back End you will help design, build, and optimize Distillery—our AI-native platform that powers real-world enterprise AI systems for diverse F500 workflows.

Your role will involve developing scalable AI infrastructure, ensuring system reliability, and collaborating with engineers and business leaders to solve some of the most complex AI deployment challenges.

Key Responsibilities
  • Build & Scale AI-Native Infrastructure: Develop and refine a platform where AI builds, optimizes, and operates AI-powered workflows. Define how AI automation integrates into traditional enterprise infrastructure.

  • Develop Cloud-Native Microservices & Scalable AI Systems: Design and build secure, high-performance backend services deployed across AWS/GCP/Azure or on-prem Kubernetes environments. Build using Python, FastAPI, SQLAlchemy, Alembic, and modern DevOps tools to develop scalable, reliable AI infrastructure.

  • Optimize System Performance & Reliability: Ensure high-availability, security, and observability of AI-native workflows. Implement best practices for ML/AI Ops, distributed computing, and scalable service orchestration.

  • Collaborate with Cross-Functional Teams: Partner with Forward-Deployed Engineers (FDEs), AI Researchers, and business SMEs to translate real-world operational needs into platform capabilities. Advocate for strong software engineering and DevOps practices, driving high coding standards and scalable architectures.

Who You Are
  • We are hiring multiple roles across different levels of seniority (3-10+ years of software engineering experience)

  • Proficiency in Backend & Systems Engineering. Expertise in Python, Java, Golang, or C++ for building scalable, high-performance systems

  • Hands-on experience with Kubernetes, CI/CD, cloud platforms (AWS, GCP, or Azure), and infrastructure as code

  • Strong interest in AI-native development, leveraging tools like ChatGPT, Claude, Perplexity, and Cursor in engineering workflows

  • Experience with security, distributed systems, storage, ML/AI Ops, and large-scale observability is a plus

  • Travel: Ability to travel 10-20%

What We Offer
  • The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package

  • 100% covered medical, dental, and vision for employees and dependents

  • 401(k) with additional perks (e.g., commuter benefits, in‑office lunch)

  • Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems

  • Ownership of high‑impact projects across top enterprises

  • A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.

We’re grateful for the strong interest in this role. The best way to get your profile in front of our team is to apply directly through our careers page, where all applications are reviewed. Due to the high volume of interest, we’re not able to review or respond to all direct emails or LinkedIn messages. We will be in touch with every applicant once we’ve completed our review, regardless of the decision.

We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.

Skills Required

  • 3-10+ years of software engineering experience
  • Expertise in Python, Java, Golang, or C++
  • Hands-on experience with Kubernetes, CI/CD, and cloud platforms
  • Strong interest in AI-native development
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The Company
HQ: San Francisco, California
45 Employees

What We Do

Distyl AI is on a mission to create the most customer-centric AI company that revolutionizes how enterprises thrive in the AI-assisted economy. We collaborate with leading institutions worldwide to enhance their AI readiness and build dependable, seamlessly integrated AI-driven solutions tailored to their distinct data, workflows, and employee requirements. Using our proprietary platform of in-house tools and alliances such as the one with OpenAI, our team diligently develops and deploys generative AI products that adhere to the highest standards of integrity and reliability, empowering the institutions that require them the most.

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