About the role 

The Senior Integration, API & Automation Engineer is a hands-on technical lead role responsible for shaping and executing Rubrik’s enterprise API, integration, and AI‑driven automation strategy.

Broadly, the role will focus on designing, building, and governing secure, scalable APIs and integrations between our core business platforms and third‑party systems (e.g., ERP, HCM, CRM, data platforms), while mentoring engineers and driving best practices across the organization. In addition, this role will help us embed AI capabilities (LLMs, Claude, decisioning services, intelligent workflows) into APIs and business processes to improve reliability, productivity, and insight.

You will work closely with senior business stakeholders, application owners, security, data, and IT teams to define API‑first, AI‑aware integration patterns and standards that deliver robust, secure, real‑time and batch integrations using REST APIs, webhooks, messaging, file‑based interfaces, and AI services.

This role will primarily leverage MuleSoft Anypoint Platform (or similar iPaaS) for API‑led connectivity and sits within the Enterprise Integrations & Intelligent Automations team as a key technical authority.

What you'll do

• Own the API and integration architecture and strategy for assigned domains, defining API‑led patterns (Experience, Process, and System APIs), reference architectures, and standards for how systems integrate across the enterprise.
• Design, build, and evolve RESTful APIs that expose well‑designed resources and operations to internal and external consumers, with clear contracts, documentation, and SLAs.
• Lead implementation of integrations between SaaS and on‑prem applications (e.g., NetSuite, Workday, Salesforce, Snowflake, ServiceNow), Finance, HR, Security, and GTM platforms, ensuring solutions are scalable, secure, resilient, and observable.
• Create data integration strategies for high volumes of data in transit, optimizing for performance, reliability, and cost (e.g., streaming vs. batch, push vs. pull APIs, caching, backoff strategies).
• Define and enforce API governance, including:
• Provide technical leadership to integration and API engineers, including solutioning, design reviews, code reviews, and mentoring of junior and contract engineers.
• Implement and manage REST/SOAP APIs, webhooks, and messaging interfaces from conceptual design through development, performance testing, deployment, and lifecycle management via an API gateway or iPaaS (e.g., MuleSoft Anypoint Platform).
• Architect robust data integrations for both real‑time and scheduled (batch) workloads using APIs, messaging, sFTP, and file‑based exchanges (JSON, XML, CSV), with well‑defined contracts, SLAs, and monitoring.
• Define non‑functional requirements (NFRs) and SLAs for APIs and integrations—availability, latency, throughput, error budgets, RTO/RPO—and ensure designs and implementations meet or exceed them.
• Drive observability and reliability for APIs and integrations by standardizing logging, tracing, metrics, dashboards, and alerting, and by creating operational runbooks for incident response and post‑incident reviews.

AI & Intelligent Automation Responsibilities

• Identify and prioritize AI opportunities within API and integration flows (e.g., data enrichment, anomaly detection, routing, summarization, classification, intent extraction).
• Define safe and governed AI usage within APIs and integrations, including:
• Clear input/output contracts for AI services
• Guardrails (prompt design, validation, constraints)
• Handling of sensitive data (PII/financial/HR data) in prompts and responses
• Monitoring for model performance and drift in production.
• Integrate with AI platforms and services (internal or external), including model APIs, vector stores, and feature stores, using strong API design and security practices.

Stakeholder, Security, and Platform Responsibilities

• Partner with security, compliance, and audit teams to ensure integrations, APIs, and AI services meet security, privacy, and regulatory requirements (e.g., SOX‑sensitive data flows, access control, encryption, audit trails).
• Lead technical discovery and solution design for new API, integration, and AI‑automation initiatives, working with product managers, application owners, and business stakeholders to shape requirements and translate them into well‑defined technical designs.
• Own vendor and platform technical relationships for integration technologies and key SaaS systems; understand vendor APIs and change roadmaps, anticipate the impact of deprecations, and coordinate upgrades and migrations.
• Oversee CI/CD practices for APIs, integrations, and AI services, including branching and release strategies, automated testing (unit, integration, regression), and environment configuration management for Dev/QA/UAT/Prod.
• Champion reuse and standardization by building and curating shared assets such as:
• Generic APIs (e.g., email, JIRA, logging, AI utility services)
• Common connectors and API client libraries
• Templates and integration catalogs
  and ensuring they are adopted broadly.
• Participate in and improve KTLO/on‑call rotations for critical APIs, integrations, and AI services, using incident data to drive structural improvements, technical debt reduction, and increased reliability.
• Communicate clearly with technical and non‑technical audiences, producing architecture diagrams, decision records, and documentation that make complex API, integration, and AI solutions easy to understand, operate, and evolve.

Experience you'll need

• Education & Experience

  • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
  • 10+ years of overall software/integration engineering experience, with 8+ years focused on API and enterprise integrations.
  • 4+ years in a senior/lead/architect capacity, owning API and integration designs, patterns, and technical decisions for complex cross‑system and enterprise application solutions.
  • Experience designing and delivering AI‑enabled features or workflows as part of production systems (e.g., integrating with LLM or ML APIs, AI‑based decisioning, or intelligent automation).

Technical Skills – API Engineering

• Deep expertise in RESTful API design and implementation, including:
• Resource modeling, URI design, and standard HTTP methods
• API‑first/contract‑first design (RAML/OpenAPI)
• Pagination, filtering, sorting, and partial responses
• Versioning strategies (URL, header, content negotiation)
• Idempotency and robust error handling patterns.
• Strong experience building secure, resilient, and scalable APIs, including:
• API gateways (e.g., MuleSoft, Apigee, Kong, AWS API Gateway)
• Rate limiting, throttling, caching, and circuit‑breaker patterns
• Timeout, retry, and backoff strategies.
• Solid understanding of webhooks and event‑driven APIs, including subscription management, signature validation, replay protection, and idempotent consumers.
• Hands-on experience with API client development and integration patterns (SDKs, service‑to‑service communication, backend‑for‑frontend, composite APIs).

Technical Skills – Integration & Platforms

• Strong experience with MuleSoft Anypoint Platform (or equivalent iPaaS), including API Manager, Runtime Manager/CloudHub, Anypoint Exchange, and design/deployment best practices.
• Solid understanding of SOAP services, messaging patterns (pub/sub, event‑driven integrations), and when to apply each.
• Proficiency with integration data formats and transformation (JSON, XML, CSV, mapping, enrichment, aggregation, canonical models).
• Strong database and data modeling skills, including SQL and working with relational databases (e.g., Postgres, SQL Server, Oracle) in integration scenarios.
• Experience designing and implementing secure integrations, including:
• OAuth 2.0/OpenID Connect
• API keys and mutual TLS
• Role/permission models and fine‑grained authorization
• Secrets management (e.g., HashiCorp Vault, cloud KMS).
• Hands‑on experience with CI/CD pipelines and Git‑based workflows, including automated testing, static analysis, deployment automation, and environment configuration for API and integration services.
• Demonstrated experience integrating with several of the following: NetSuite, Workday, Salesforce, Snowflake, ServiceNow, Coupa, DocuSign, ChromeRiver, Marketo, identity/IAM platforms, external APIs, and internal APIs.
• Practical experience working with AI/ML or LLM APIs (e.g., OpenAI, Azure OpenAI, Vertex AI, Bedrock, or internal model APIs), including:
• Designing API requests and responses for AI‑backed features
• Prompt engineering and response validation
• Handling rate limits, retries, timeouts, and partial failures within integration flows.
• Familiarity with event‑driven and streaming architectures (e.g., Kafka, EventBridge, Event Hubs) and how to combine them with AI services for near real‑time decisioning and automation.

Soft Skills

• Proven ability to lead without direct authority, influencing cross‑functional teams and driving technical decisions through clarity and data rather than hierarchy.
• Strong architectural thinking and problem‑solving skills, including the ability to decompose complex business processes into robust API, integration, and AI‑enabled designs.
• Excellent communication and documentation skills, comfortable presenting solutions and trade‑offs to engineers, managers, and senior business stakeholders.
• Experience working in agile environments, collaborating closely with product owners, scrum teams, and distributed stakeholders across time zones.
• Bias toward automation, standardization, and continuous improvement, with a pragmatic approach to balancing speed, risk, and long‑term maintainability.

Preferred Qualifications

• Professional MuleSoft certifications (e.g., MuleSoft Certified Integration Architect, MuleSoft Certified Developer) or equivalent certifications from other integration platforms.
• Experience designing and operating public or partner-facing APIs with clear productization (API lifecycle, developer experience, SLAs, and commercial considerations).
• Experience designing and operating integrations in regulated or security‑sensitive environments (e.g., SOX, FedRAMP, customer‑facing APIs) with a strong emphasis on auditability and change control.
• Experience with event‑driven and streaming platforms (e.g., Kafka, AWS EventBridge, Azure Event Hubs) and their role in modern API and integration architectures.
• Exposure to automation/workflow platforms (e.g., Zapier, Workato, low‑code tools) and how they complement enterprise integration layers and AI‑based automation.
• Experience building and maintaining API and integration runbooks, catalogs, and governance processes, and contributing to enterprise architecture forums or design reviews.
• Experience with observability stacks (e.g., Datadog, Splunk, New Relic, OpenTelemetry) for monitoring APIs, integrations, and AI services in production.
• Familiarity with data and AI governance concepts (e.g., data classification, lineage, model governance, responsible AI practices) and how they apply within API, integration, and automation patterns.

About the Role

We are looking for a Senior Staff Software Engineer to join the Veeam Data Cloud (VDC) engineering team at its highest individual contributor tier. In this role, you will shape the long-term technical direction of VDC, operating with organization-wide scope and influence. You will define architectural standards, resolve the most complex and ambiguous engineering challenges, and mentor a generation of Staff and senior engineers.

This is a rare opportunity to be a founding technical voice on greenfield projects — designing next-generation data protection services that will be deployed and relied upon worldwide. You will be a trusted partner to engineering leadership, product management, and cross-functional stakeholders, bridging technical excellence with business strategy.

What You’ll Do

• Technical Strategy & Architecture

  • Own and drive the multi-year technical roadmap for the Veeam Data Cloud platform, aligning engineering decisions with company strategy.
  • Define, communicate, and enforce architectural standards, design patterns, and engineering principles across multiple teams and product areas.
  • Lead architectural reviews for major systems, proactively identifying structural risks and establishing long-term scalability and resilience frameworks.
  • Author foundational technical design documents (RFCs, ADRs) that serve as the engineering blueprint for the broader organization.

  Engineering Execution & Excellence

  • Personally contribute to the most critical, highest-complexity engineering challenges across the organization — including those that span team boundaries.
  • Design and develop highly reliable, planet-scale SaaS microservices integrated with managed cloud services (Azure, AWS, GCP) using Golang and modern cloud-native patterns.
  • Establish and champion engineering quality standards: testing philosophy, observability, performance benchmarks, security posture, and release reliability.
  • Drive the adoption of emerging engineering practices — including AI-powered developer tooling, automated code generation, and LLM-assisted testing and debugging.

  Organizational Leadership & Influence

  • Serve as the primary technical escalation point across engineering — resolving the most ambiguous, cross-cutting problems that no individual team can own alone.
  • Partner with engineering managers and directors to set execution standards, unblock delivery, and ensure timely, predictable outcomes across multiple teams.
  • Represent engineering in cross-functional leadership forums (product, security, infrastructure, finance) and act as a decision-maker on technical trade-offs with business impact.
  • Drive the organization-wide engineering culture: nurturing psychological safety, technical curiosity, and a bias toward measurable outcomes.

  Mentorship & Talent Development

  • Provide deep technical mentorship to Staff, Senior, and mid-level engineers, accelerating their growth and expanding team capability.
  • Lead structured technical coaching, design review sessions, and architectural war-games to sharpen engineering judgment across the organization.
  • Identify, recruit, and help retain top engineering talent; actively shape the interview process and hiring bar for senior roles.

  Operational Ownership

  • Participate in on-call rotation and lead incident response for critical production events, driving root cause analysis and systematic resolution.
  • Own post-incident reviews and embed learnings into platform improvements and operational runbooks.

What You’ll Bring

• 15+ years of progressive software engineering experience, with a proven track record as a principal-level individual contributor.
• Demonstrated expertise designing, building, and operating SaaS or large-scale cloud services on Azure, AWS, or GCP at organization-defining scale.
• Deep expertise in Go (Golang) and/or other systems-grade modern languages (C#, Java, Rust, Scala); polyglot mindset with language-agnostic design thinking.
• Mastery of distributed systems: event-driven architecture, eventual consistency, high-availability design, and fault-tolerant microservices.
• Expert-level command of container orchestration (Kubernetes, Docker) and cloud-native infrastructure patterns.
• Exceptional communication and leadership skills — able to drive clarity and alignment across engineering, product, and executive audiences.
• Strong computer science fundamentals: data structures, algorithms, concurrency, and systems design.
• A track record of delivering greenfield projects from zero to production at scale, with full ownership of quality, security, and reliability.

Bonus Skills

• Experience leveraging AI capabilities (LLMs, generative AI, co-pilot tooling) in product development workflows — either as a feature builder or as a force-multiplier for engineering productivity. 
• Hands-on experience building AI-powered features into SaaS products: integrating model APIs, designing prompt pipelines, or building AI-assisted developer experiences.
• Background in data protection, backup, disaster recovery, or storage infrastructure.
• Experience in platform or infrastructure engineering serving other engineering teams as internal customers.

What You’ll Get

• 18 paid vacation days, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Private medical coverage for you and up to four dependents
• Life, accident, and disability insurance with enhanced coverage
• Annual flexible wellbeing allowance for physical and mental wellness
• Free confidential counselling and coaching via Employee Assistance Program (EAP), including legal and financial advice
• Meal, fuel, and transportation benefits based on work arrangement
• Daycare reimbursement and safe cab facility for eligible employees
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

Please note: If the applicant is permanently located outside India, Veeam reserves the right to decline the application. 

#LI-KP1

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

• Timing Convergence Leadership: Drive full-chip SOC timing closure across all corners and modes (func, shift, capture, etc.).
• Cross-Functional Coordination: Partner with Architecture to validate timing feasibility, RTL to optimize logic structures, and DFT to streamline test-mode timing.
• Left-Shift Strategy: Proactively identify and resolve structural timing issues, congestion, and high-latency paths early in the RTL/Synthesis phase to ensure predictable physical design execution.
• Advanced Analysis: Perform complex timing tasks including CPPR/CRPR analysis, NoC (Network-on-Chip) timing, and constraint validation (SDC).
• Automation & Agility: Architect and build sophisticated automation utilities (Tcl, Python, Perl) to accelerate timing sign-off, reduce manual audits, and improve schedule agility.
• PPA Optimization: Drive best-in-class PPA by guiding physical design teams on floorplanning, clock tree synthesis (CTS) strategies, and placement optimizations.

• Experience: 9 to 14 years of hands-on experience in STA and Timing Closure on advanced process nodes (7nm, 5nm, or below).
• Critical Thinking: Proven ability to debug complex timing violations, identify root causes (e.g., data-to-clock skew, crosstalk), and propose architectural or physical solutions.
• Technical Mastery: * Expertise in industry-standard sign-off tools (e.g., PrimeTime, Tempus). Preferable Tempus tool.
• Deep understanding of Multi-Mode Multi-Corner (MMMC) challenges and Hierarchical vs. Flat timing closure.
• Proficiency in SDC/CDC constraints.
• Soft Skills: Strong leadership presence with the ability to influence cross-functional teams and drive execution in a fast-paced environment.
• Education: B.Tech/M.Tech in Electrical/Electronics Engineering or a related field.

What You Will Do and Learn

As a Data Engineer in Data Solutions, you’ll be responsible for designing, implementing, and testing proposed modern analytic solutions.  Working closely with our client partners and architects, you’ll develop relationships with key technical resources while delivering tangible business outcomes. 

Qualifications:

· 2-4 years’ experience developing industry leading business intelligence and analytic solutions

· Must have thorough knowledge of data warehouse concepts and dimensional modelling

· Must have experience in writing advanced SQL

· Must have at least 2+ years of hands-on experience on DBT (Data Build Tool). Mandatory to have most recent hands-on experience on DBT.

· Must have experience working with DBT on one or more of the modern databases like Snowflake / Amazon Redshift / BigQuery / Databricks / etc.

· Hands-on experience with Snowflake would carry higher weightage

· Snowflake SnowPro Core certification would carry higher weightage

· Experience working in AWS, Azure, GCP or similar cloud data platform would be an added advantage

· Hands-on experience on Azure would carry higher weightage

· Must have experience in setting up DBT projects

· Must have experience in understanding / creating / modifying & optimizing YML files within DBT

· Must have experience in implementing and managing data models using DBT, ensuring efficient and scalable data transformations

· Must have experience with various materialization techniques within DBT

· Must have experience in writing & executing DBT Test cases

· Must have experience in setting up DBT environments

· Must have experience in setting up DBT Jobs

· Must have experience with writing DBT Jinja and Macros

· Must have experience in creating DBT Snapshots

· Must have experience in creating & managing incremental models using DBT

· Must have experience with DBT Docs

· Should have a good understanding of DBT Seeds

· Must have experience with DBT Deployment

· Must Experience with architecting data pipelines using DBT, utilizing advanced DBT features

· Proficiency in version control systems and CI/CD

· Must have hands-on experience configuring DBT with one or more version control systems like Azure DevOps / Github / Gitlab / etc.

· Must have experience in PR approval workflow

· Participate in code reviews and best practices for SQL and DBT development

· Experience working with visualization tools such as Tableau, PowerBI, Looker and other similar analytic tools would be an added advantage

· 2+ years of Business Data Analyst experience

· 2+ years of experience writing Business requirements, Use cases and/or user stories, for data warehouse or data mart initiatives.

· Understanding and experience on ETL/ELT is an added advantage

· 2+ years of consulting experience working on project-based delivery using Software Development Life Cycle (SDLC)

· 2+ years of years of experience with relational databases (Postgres, MySQL, SQL Server, Oracle, Teradata etc.)

· 2+ years of experience creating functional test cases and supporting user acceptance testing

· 2+ years of experience in Agile/Kanban/DevOps Delivery

· Outstanding analytical, communication, and interpersonal skills

· Ability to manage projects and teams against planned work

· Responsible for managing the day-to-day client relationship on projects

· Manage the Data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance

· Collaborate with team members to design and implement technology that aligns with client business objectives

· Build proof of concepts for a modern analytics stack supporting a variety of Cloud-based Business Systems for potential clients

· Team management experience and ability to manage, mentor and develop talent of assigned junior resources

· Create actionable recommendations based on identified platform, structural and/or logic problems

· Communicate and demonstrate a clear understanding of client business needs, goals, and objectives

· Collaborate with other architects on solution designs and recommendations.