Responsibilities
- Own the architecture and technical direction for key product areas in a multi-tenant SaaS platform.
- Work with product, design, and data/ML teams to translate business problems into simple, robust technical solutions.
- Drive the evolution of our system architecture (APIs, services, data flows, auth, tenancy, integrations) as the product and customer base scale.
- End-to-End Full-Stack Product Delivery
- Build and maintain backend services and APIs (REST/GraphQL/gRPC) that power those experiences.
- Deliver backend features end-to-end including data schemas and business logic.
- Collaborate with UX and product to ensure responsive and delightful product experiences.
- Data / ML / AI Integration
- Partner with data scientists and MLOps / platform teams to embed data, ML and AI capabilities into the product (recommendations, categorization, automation, routing, insights, LLM-powered workflows, etc.).
- Design APIs, data contracts, and UX flows that make ML/AI features reliable, understandable, and safe for customers.
- Ensure telemetry and feedback loops are in place so data/ML teams can measure performance, iterate models, and improve outcomes.
- Help define and implement guardrails for AI features (fallbacks, explanations, error handling, permissions).
- Operational Excellence
- Champion operability: monitoring, alerting, logging, and runbooks for services you own.
- Lead efforts to improve performance, scalability, and resilience of critical paths (e.g., onboarding, reporting, AI-assisted workflows).
- Work with security and compliance to ensure features meet requirements around authentication, authorization, data privacy, and multi-tenancy.
- Participate in and help evolve on-call / incident response processes as a technical leader.
- Engineering Excellence & Leadership
- Act as a technical mentor for multiple teams, raising the bar on code quality, reviews, testing, and design.
- Lead technical design reviews and cross-team architecture discussions, especially where product, data, and ML intersect.
- Help define engineering standards and best practices (API design, frontend patterns, error handling, observability, testing).
- Partner with engineering management to shape roadmaps, staffing, and sequencing for major initiatives.
Requirements
- 10+ years of software engineering experience
- Demonstrated experience shipping data/ML/AI powered SaaS products
- Strong track record of owning and shipping complex, user-facing features end-to-end in collaboration with product management and UX.
- Experience as a senior member of the technical staff in guiding teams and owning critical production systems.
- Strong proficiency with at least one backend stack, for example: Node.js/TypeScript, Java, Go, Rust, or similar
- Designing and building APIs, services, and integrations
- Proficiency with Python and data analysis/modeling tools (e.g. pandas/pytorch)
- Solid understanding of data modeling and storage: relational databases, caching, and basic data warehousing concepts.
- Familiarity with data/ML/AI concepts: How ML models or LLMs are exposed as services
- Typical failure modes, latency/throughput considerations, and guardrails
- Experience with cloud platforms (AWS / GCP / Azure), containers, and infrastructure (networking, scaling, security).
- Strong habits around testing, CI/CD, code reviews, and incremental delivery.
