Senior Software Engineer, Sybill
Backend, Systems & Product
$180-240k
+ Equity
Office located in Mountain View, CA
Sales intelligence & automation
Be an early applicant
Sales intelligence & automation
21-100 employees
Be an early applicant
$180-240k
+ Equity
Office located in Mountain View, CA
21-100 employees
Company mission
To empower B2B reps to sell twice as much.
Role
Who you are
- Deep understanding of distributed systems and scalable architectures
- Strong experience with data storage systems (PostgreSQL, Redis, S3)
- Expertise with queueing/streaming systems (Kafka, SQS)
- Solid grasp of system design patterns and tradeoffs
- Experience building high-throughput, low-latency services
- Track record of shipping complex backend features end-to-end
- Strong programming fundamentals and code quality
- Experience with Python and modern web frameworks (FastAPI)
- Understanding of AI/ML systems integration
- Ability to translate customer requirements into technical solutions
- BS/MS in Computer Science from a top US university
- 5+ years of hands-on backend development experience
- Proven track record as a technical owner at a fast-paced startup
- Strong bias for action and ability to ship with minimal direction
- Available to work 4+ days/week in Mountain View
Desirable
- Track record of building 0→1 products and seeing them scale
- Experience with AI/ML infrastructure and large-scale data processing
- History of high-impact technical decisions that drove product success
- Ability to mentor others on system design and architecture
What the job involves
- We're seeking a senior backend engineer who combines strong computer science fundamentals with high ownership and customer focus
- You'll be designing and implementing scalable systems that power our core product features, working at the intersection of distributed systems and AI infrastructure
- Design and implement end-to-end backend systems with high reliability and performance
- Build and scale core infrastructure powering our AI features
- Drive critical technical decisions that impact product architecture
- Work directly with customers to understand their needs and ship solutions
- Ensure operational excellence with minimal to zero downtime
Our take
To help sales teams maximise their time, Sybill provides an AI that reduces the time spent on administrative tasks so that they can instead focus on building client relationships.
It's a simple but effective proposition. Sybill's AI can take deal notes, draft tone-correct follow-up emails and write process-aware CRM updates. Its model was built specifically for sales, making it a better option than more generic AI admin tools.
The company has raised significant funds, the latest of which will be used to further the development of its AI and build out its team. With upwards of 500 paying customers, the company has got off to a great start and is set up nicely for future growth.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
Company
Funding (last 2 of 3 rounds)
Jul 2024
$11m
SERIES A
Jul 2023
$2m
SEED
Total funding: $14.6m
Company HQ
Old Mountain View, Mountain View, CA
Articles
Leadership
Gorish Aggarwal
(Co-Founder & CEO)Previously a Lecturer at the Stanford University School of Engineering, and a Graduate Research Assistant at the Stanford University School of Medicine. Also worked as a Data Scientist for Lightspeed Venture Partners.
Mehak Aggarwal
(Co-Founder & CPO)Previously a Research Fellow at Harvard University, The Hebrew University of Jerusalem and Singapore University of Technology and Design. Has previously developed several AI-based projects.
Soumyarka Mondal
(Co-Founder & CTO)Official Member of the Forbes Technology Council. Former Platform Engineer for Confluen, Graduate Teaching Assistant at the University of California San Diego and Software Engineer Intern at Salesforce.
Nishit Asnani
(Co-Founder)Previously a Teaching Assistant at Stanford University. Also interned in ML and Project Management at Moveworks, co-founded Wordsmith and was a Graduate Student Researcher at the Stanford Artificial Intelligence Laboratory.
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