We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• 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. 

What You’ll Bring 

Experience 

• 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. 

Technical Skills 

• 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. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

Role Overview 

We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• 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. 

What You’ll Bring 

Experience 

• 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. 

Technical Skills 

• 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. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

Role Overview 

We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI. 

You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to: 

• Ship high-quality data/ML/AI powered features end-to-end 

• Integrate data/ML/AI capabilities into real customer workflows 

• Raise the bar on design, reliability, performance, and engineering practices across the org 

This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams. 

What You’ll Do 

• 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. 

What You’ll Bring 

Experience 

• 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. 

Technical Skills 

• 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. 

Mindset & Soft Skills 

• Product-minded engineer who cares about customer problems, usability, and outcomes, not just code. 

• Systems thinker who can balance short-term delivery with long-term architectural health. 

• Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams. 

• Enjoys mentoring and multiplying the impact of other engineers. 

We’re hiring Applied ML Engineers to partner with multiple product teams to extract insights from data and build AI-powered features and automated workflows across the product suite. 

In this role, you will both: 

• Enable product teams: teach, coach, and guide them on data and ML best practices 

• Lead by example: do complex data analysis and ML modeling, architecture, and implementation work as needed to accelerate teams while mentoring more junior data/ML folks. 

You’ll own the data analysis, ML modeling, and workflow logic that let AI understand user requests, enrich and route them, suggest actions, and in some cases fully automate resolution.  

What You’ll Do 

Data & ML Modeling 

• Explore and analyze data using Python, pandas, and PySpark (or similar tools). 

• Use matrix factorization, clustering, dimensionality reduction, and related techniques to understand and prepare data for modeling, and to identify and label latent factors (e.g., user behavior patterns, content/topic clusters, expertise dimensions). 

• Create, tune, and productionize ML models for: 

• Categorization / classification 

• Recommendations and similarity 

• Other prediction or ranking tasks that power product features 

AI-Powered Workflows & Features 

• Design and implement AI-driven ingest flows that turn unstructured inputs (tickets, emails, forms, messages, logs, etc.) into well-structured data that models and downstream systems can use. 

• Build workflows where AI can: 

• Auto-fill or suggest key fields and metadata. 

• Proactively ask users/customers for missing or ambiguous information (e.g., via email or messaging). 

• Surface similar past items or solutions to assist humans in decision-making. 

• Fully handle simple, repetitive “Level 1” style requests end-to-end when safe to do so. 

• Work closely with engineers to integrate models and workflows into production systems with proper monitoring, fallbacks, and guardrails. 

Cross-Team Leadership & Enablement 

• Work with multiple product teams to help them identify and scope AI opportunities in their areas. 

• Define patterns, templates, and best practices for data ingestion, feature creation, model usage, and evaluation that teams can reuse. 

• Serve as a trusted advisor and technical lead: 

• Provide design and architecture guidance on data and ML-heavy features. 

• Join projects to handle the most complex modeling or workflow automation pieces when teams get stuck. 

• Mentor and guide junior data/ML engineers and analysts: 

• Conduct code and model reviews. 

• Pair with them on tricky problems. 

• Help them develop good intuitions about metrics, evaluation, and operational reliability. 

• Help establish and socialize standards for experimentation, documentation, and responsible AI usage across teams. 

What You’ll Bring 

Core Skills 

• 5+ years in data science, ML engineering, or a similar applied role, with a strong record of shipping production data/ML features. 

• Strong Python skills and experience with pandas for data analysis. 

• Experience with PySpark or other distributed data processing frameworks. 

• Solid understanding of ML fundamentals, including: 

• Supervised learning and classification models 

• Matrix factorization / embeddings / latent factor models 

• Feature engineering and model evaluation (offline metrics and online experiments) 

• Proficiency with PyTorch (or a similar deep learning framework) and related ML tooling. 

• Strong SQL and experience with modern data warehouses / data lakes. 

• Comfort working with APIs, microservices, and production integration of ML models, including performance and reliability considerations. 

Leadership & Collaboration 

• Experience serving as a technical lead or senior individual contributor across multiple teams or projects. 

• Proven ability to translate business problems into data/ML projects, and to clearly explain tradeoffs to non-ML stakeholders. 

• Track record of mentoring junior engineers/analysts and improving team practices (e.g., review culture, testing, monitoring). 

• Strong communication skills and the ability to drive alignment across product, engineering, and operations. 

Nice to Have 

• Experience with LLMs and language-centric workflows (RAG, prompt engineering, fine-tuning, tool/agent orchestration). 

• Experience building agent-assist features or automated workflows in operational or customer-facing products. 

• Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex, etc.) and production model monitoring. 

• Prior experience in a platform/enablement role, supporting many product teams with shared data and ML capabilities. 

Role Overview:

• This is a foundational leadership role; the work here impacts how every product, customer, and partner experiences Kaseya. Role will be responsible for building and executing the Identity and API strategy for Kaseya's platform.  
• This position demands deep technical expertise in Identity platforms combined with strategic product thinking and cross-functional collaboration. 
• This role will work closely with product, security, legal, sales, and marketing teams across the organization to build foundational capabilities that become force multipliers for the entire platform. 
• This role shapes the core platform layer that enables engineering teams to build, automate, and operate software and AI-enabled systems reliably at scale.  

What will you do:

What You'll Do As a Principal Engineer, you will be the technical north star for our IAM and Control Plane strategy. Your role transcends individual features; you will be responsible for the long-term health and architectural evolution of our identity systems. Own the end‑to‑end technical design of IAM services, including identity lifecycle management, authentication, authorization, SSO, and privileged access controls, ensuring they are secure, scalable, and highly available. 

• Architectural Leadership: Lead the design and evolution of a secure, high-throughput, low-latency IAM systems that power both customer-facing and internal service APIs. Lead design and implementation of IAM integrations for SaaS, on‑prem, and cloud platforms, including federation (SAML, OIDC, OAuth), MFA, and Passwordless capabilities.
• Technical Strategy: Define the roadmap for migrating or scaling our legacy authentication and authorization systems into modern, distributed architectures.
• Cross-Functional Influence: Work closely with Product, Security, and UX teams to translate complex business requirements into robust, secure technical specifications.
• Mentorship & Excellence: Set the standard for engineering excellence through deep code reviews, technical design documents, and mentoring senior engineers.
• Operational Stewardship: Oversee the reliability of a platform under constant load, ensuring observability and resilience are baked into the core of the system.  

Required Skills:

• Extensive Experience: 10+ years of professional experience building and managing software applications at a massive scale (with at least 5 years at Sr Staff or Principal level).
• Identity Domain Expertise: Deep understanding of IAM protocols (OAuth2, OIDC, SAML), RBAC/ABAC models, and the security implications of session management at the edge. Experience with Active Directory and extensive experience implementing federation protocols (SAML, OIDC, OAuth2).
• Experience in Data Security or related areas and expertise in following--Authentication, Network, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus.
• Distributed Systems Mastery: Proven track record in designing, architecting, and debugging large-scale distributed systems that handle global traffic.
• Language Proficiency: Deep knowledge of Go, Java, TypeScript, Rust, or similar is highly valued.
• API Stewardship: Significant experience designing and versioning public-facing APIs that are used by millions of developers.
• Recruit and mentor top-tier engineering talent to scale our security infrastructure. 

Desirable Skills:

• Observability Advocate: A passion for building "observable" systems using Prometheus, Grafana, and Kibana to proactively identify failures.
• Infrastructure as Code: Experience with modern containerized deployment (Docker & Kubernetes), Terraform, and infrastructure automation.
• Security Mindset: A background in security engineering or formal verification of protocol implementations.
• Strategic Delivery: A history of leading multi-quarter projects from conception to global rollout in partnership with product owners.  

Job Title:

Senior Engineering Manager, Data Platform & AI

Why Kaseya?

Join a fast-growing company that’s transforming the IT industry. At Kaseya, you’ll have the opportunity to work with cutting-edge technology, collaborate with a dynamic team, and develop your career in a high-impact role.

Job Summary

We’re hiring a Senior Engineering Manager to lead the development of our data platform and API layer supporting Kaseya’s unified intelligence initiatives. This role is responsible for building and scaling systems that power analytics, automation, and AI-driven features across our product portfolio. You’ll lead a team of engineers, drive delivery of platform capabilities, and work closely with Product and Architecture to turn business needs into reliable, scalable systems. Success in this role means delivering high-impact platform services while improving team execution and system performance over time.

Roles & Responsibilities

• Lead a team of engineers to deliver data platform, API, and AI-related services aligned to product and company priorities
• Own delivery of key platform initiatives, ensuring systems are scalable, reliable, and meet performance expectations
• Work with Product and Architecture to define technical approaches and break down requirements into deliverable work
• Drive engineering standards across the team, including code quality, testing, and operational practices
• Partner with cross-functional teams (Product, GTM, Security, Legal) to support delivery and adoption of platform capabilities
• Improve system performance and reliability through monitoring, incident response, and ongoing optimization
• Support modernization efforts, including reducing technical debt and improving development velocity
• Track and report on delivery, system performance, and operational metrics for owned services

Required Qualifications

• 10+ years of software engineering experience, including building and operating distributed systems in production
• 3+ years of experience managing engineering teams (hiring, performance management, delivery ownership)
• Hands-on experience building or supporting data platforms, API platforms, or backend systems in a cloud environment (AWS, Azure, or GCP)
• Experience delivering production systems that handle large-scale data processing or high-throughput APIs
• Ability to translate product requirements into technical plans and deliver against defined timelines

Preferred Qualifications

• Experience working with data pipelines, analytics platforms, or AI/ML systems
• Experience building or supporting customer data platforms or telemetry systems
• Familiarity with microservices architecture and event-driven systems
• Experience improving engineering processes and team efficiency in a growing organization
• Experience working in cross-functional environments with Product, Security, and GTM teams
• Background in SaaS or platform-based products

Additional Information

Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.