Staff Backend Engineer

Job description

Staff Engineer

at Suki (View all jobs)

Bangalore, India

What we want to accomplish and why we need you

Suki is revolutionizing the health tech space with its Assistant and Platform products. We aim to create a seamless voice user interface for healthcare, freeing doctors from time-consuming administrative tasks. What does that mean? Currently, doctors use their electronic medical record system to track patient encounters (a digital version of the old paper charts you used to see in your doctor’s office and on TV). These systems can be hard to navigate and very time consuming to manage – time that doctors would rather have to spend with their patients. This is the problem we’re solving right now! Doctors that use Suki already spend over 50% less time on administrative tasks and we’re striving to do even better.

Suki is creating a new category in the health tech space. We are going to be the voice user interface for healthcare. We are creating engaging product experiences, building applications and services that delight and empower doctors with experiences that they could never imagine with their health IT systems. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine and even how medicine is practiced.  We’re a GCP shop and 100% container-run using Kubernetes.  Our tech stack includes Golang, Python, React, React Native, Swift, Android, Java, Kotlin, and JavaScript. We are seeking talented Software Developers with a strong background in Python and ML Engineering to join our team and help us build scalable, efficient, and impactful solutions.

What will you do every day?

We are looking for strong Staff Engineers to join our Backend Engineering team, with exposure to Machine Learning or Data Engineering. As a Staff Engineer, you are a technical pillar for the entire engineering organization. You will leverage your deep expertise in both Backend systems and ML Inference systems to multiply the impact of our teams and define what’s next for our technology.

• Lead Unified Technical Strategy: Define and drive the architectural vision for Suki’s backend, data and ML inference platforms. Create the roadmap for how we build, deploy, and scale everything from core microservices to our most advanced model serving and data infrastructure.
• Architect for AI at Scale: Lead the design of robust, highly scalable systems for both our core backend (in Go and Python) and our ML infrastructure, including real-time inference APIs, offline training pipelines, data processing, and GPU orchestration.
• Solve the Hardest Problems: Tackle the company’s most complex and ambiguous technical challenges that sit at the intersection of distributed systems and applied AI. You will break down these problems and guide multiple teams toward elegant and practical solutions.
• Bridge Research and Production: Serve as the key technical link between our AI/ML Research teams and our Backend platform engineering teams. Translate cutting-edge model requirements (including LLMs) into efficient, production-grade services optimized for performance, cost, and reliability.
• Drive Technical Excellence & MLOps: Establish and champion best practices across the organization for system design, code quality, observability, and MLOps. Set the standard for system reliability, efficient resource utilization (CPU, memory, GPU), and CI/CD for ML.
• Mentor and Elevate the Team: Act as a role model and mentor for senior engineers across data, Backend and ML Engineering disciplines. Foster a culture of deep technical understanding and collaboration, helping to grow the next generation of technical leaders at Suki.
• Remain Hands-On: Stay deeply connected to the code by prototyping new architectures, implementing foundational components for our ML inference platform, and leading the resolution of the most critical incidents and performance bottlenecks.

What We’re Looking For

• Distinguished Technical Expertise: You are a recognized expert with a proven history of architecting, building, and operating complex systems at the nexus of backend engineering and machine learning.
• Strategic, Systems-Level Thinker: You look beyond immediate requirements to anticipate future challenges. You can navigate deep ambiguity, identify long-term risks, and make high-judgment decisions that balance technical purity with business velocity.
• Pragmatic and Action-Oriented: You have a bias for action and a data-driven approach to problem-solving. You understand the entire lifecycle of an ML-powered feature, from data to deployment, and know how to ship robust solutions quickly.
• Leadership Through Influence: You have a demonstrated ability to lead complex, cross-functional technical initiatives without direct authority. You build consensus, articulate complex ideas clearly, and are a trusted technical advisor to engineering leadership.
• A Force Multiplier: You lead with humility and find satisfaction in mentoring others. You elevate the performance and knowledge of the entire engineering organization.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
• 8+ years of professional software engineering experience, with a proven track record of operating at a Staff, Principal, or equivalent level.
• Expert-level proficiency in at least any one programming language commonly used for building distributed systems or AI-powered systems like Python or Go, with the ability to lead architectural decisions in those languages.
• Deep, demonstrable expertise in designing and operating large-scale distributed systems and microservices architectures.
• Proven experience designing and building production ML infrastructure, including model serving systems, inference APIs, data pipelines, and training/evaluation workflows.
• Good knowledge of cloud platforms (GCP preferred), containerization (Docker), and orchestration (Kubernetes).
• Strong experience optimizing backend and ML workloads for performance, latency, cost, and GPU utilization.
• Experience integrating and scaling systems that use LLM APIs or foundation models.
• Familiarity with modern API technologies like gRPC and Protocol Buffers.

Tell me more about Suki

• On a roll: Named by Fast Company as one of the most innovative companies, named Google’s Partner of the Year for AI/ML, named by Forbes as one of the top 50 companies in AI .
• Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems.

Great investors: We’re backed by Venrock, First Round Capital, Flare Capital, March Capital , and others. With our recent $70M Series D financing, we have the resources to scale.

• Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it.
• Great customers: Our solutions are used in health systems and clinics across the country, supporting clinicians across dozens of specialties.  Check out what one of our users says about how Suki has helped his practice.
• Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better.

Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.

Working at Suki:

Our hybrid model offers the perfect balance of in-office collaboration and remote flexibility which includes three days in the office (Monday, Tuesday and Wednesday) and two days work from home (Thursday and Friday).The role is located in Bangalore and will require working from office three days a week.