Top 7 Vector Database acquisition Knowledge Graph Cloud Jobs

Sr Principal/Principal Software Engineer, App
Lila Sciences —Cambridge, MA
- $204,000 - $348,000 a year
- Computer Science
- System design
- 8 years
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Senior Software Engineer, App
Lila Sciences —Cambridge, MA
- $144,000 - $240,000 a year
- Computer Science
- 5 years
- System design
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Distinguished Engineer, AI Factory
Banyan Software —Seattle, WA
- Up to $206,500 a year
- Computer Science
- System design
- Java
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Director, Knowledge Graph & Semantics - HYBRID ROLE
Vertex Pharmaceuticals —Boston, MA
- $216,400 - $324,600 a year
- Full-time
- Hybrid work
- System design
- Office
- Machine learning
- Loan repayment program
- Dental insurance
Archer Data Scientist
Archer Technologies LLC —United States
- $129,200 - $215,400 a year
- Remote
- 5 years
- System design
- US work authorization
- Health insurance
- Flexible spending account

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Sr Principal/Principal Software Engineer, App

Lila Sciences
Cambridge, MA

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Job Details

$204,000 - $348,000 a year

Qualifications

AI models
Software engineering
Scalable systems
Production systems
Collaboration with product development teams
Machine intelligence
Model deployment
Scalability
Developing and maintaining backend systems
Web applications
Front-end component implementation
Cross-functional communication

Full Job Description

Your Impact at LILA

Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineers who want to solve problems no one has solved before.

We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.

About The Team

The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results.

AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons.
The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them.
You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast.
You'll ship things that matter. The tools you build accelerate research timelines from months to days.

If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect systems that don't exist yet — we want to talk.

What You'll Be Building

Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
Hands on experience using AI coding assistants to drive productivity is required.
Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.
Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
Experience with laboratory devices, robotics, or hardware drivers.

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We're All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

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Refine Your Search

Vector Database acquisition Knowledge Graph Cloud jobs

Sr Principal/Principal Software Engineer, App

Senior Software Engineer, App

Distinguished Engineer, AI Factory

Director, Knowledge Graph & Semantics - HYBRID ROLE

Archer Data Scientist

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