About Hexnode

Hexnode is a global leader in Unified Endpoint Management (UEM), trusted in over 100 countries and managing millions of devices worldwide. With continuous innovation across Apple, Windows, Android, macOS, Linux, and tvOS ecosystems, Hexnode is redefining enterprise mobility and cybersecurity.

As we expand our Extended Detection and Response (XDR) capabilities, we are building a next-generation data platform designed for massive scale, real-time intelligence, and high-performance security analytics.

The Role

We are looking for a Senior Data Platform Engineer to architect, scale, and optimize the core data infrastructure powering our XDR product.

In this role, you will take ownership of the strategic evolution of our data layer — ensuring seamless ingestion, storage, indexing, search, and retrieval of high-volume security telemetry and device data. You will play a key role in transforming our platform into a highly scalable, cost-efficient, secure, and analytics-ready ecosystem that supports real-time detection, investigation, and advanced data science workflows.

This is a high-impact individual contributor role focused on architecture, platform modernization, and long-term scalability.

Key Responsibilities

• Architect and evolve the data layer to support high-throughput ingestion, real-time processing, and low-latency search across massive datasets.
• Evaluate existing search and storage platforms and drive modernization initiatives toward more scalable, performant, and cost-effective solutions.
• Design and implement optimized indexing, partitioning, and data structuring strategies for efficient querying and retrieval.
• Build and manage scalable data lake architectures that support advanced analytics, threat intelligence, and data science workflows.
• Define strategies for lifecycle management, retention, tiered storage, and cost optimization across the data platform.
• Ensure high availability, fault tolerance, and disaster recovery across distributed systems.
• Implement robust data security controls aligned with XDR and modern cybersecurity frameworks, ensuring data protection at rest and in transit.
• Collaborate closely with security engineering, backend teams, and data scientists to bridge raw telemetry ingestion with actionable insights.
• Continuously monitor platform performance and lead improvements in reliability, scalability, and operational efficiency.

Qualifications

• 6–10 years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Systems Architecture as an Individual Contributor.
• Strong hands-on experience with large-scale distributed search and analytics platforms.
• Proven experience evaluating and migrating data platforms to improve scalability, performance, and cost efficiency.
• Deep understanding of indexing strategies, query optimization, and distributed data storage architectures.
• Practical experience designing and operating data lake environments supporting large-scale analytics and machine learning workflows.
• Strong knowledge of data lifecycle management, storage tiering, and cost optimization strategies.
• Experience implementing security best practices in distributed data systems, especially in security or telemetry-heavy environments.
• Solid understanding of high-volume ingestion pipelines and real-time data processing systems.
• Bachelor’s degree in Computer Science, Information Technology, or a related technical field.

What We’re Looking For

• A systems thinker who can design platforms for scale, not just features.
• Someone who can balance performance, cost, and reliability in large distributed systems.
• A hands-on architect who can both define strategy and execute technically.
• Strong ownership mindset with the ability to independently drive platform-level initiatives.
• Experience working in security, cybersecurity, SIEM, or XDR environments is a strong plus.

Required Skills and Experience:

• 7+ years of experience in network engineering roles
• Relevant experience or certification (e.g. CCNP or JNCIP Data centre, Enterprise or Service provider)
• Strong knowledge of BGP, OSPF, routing policies, and network troubleshooting
• Strong understanding of TCP/IP, DNS, NAT, routing, switching, and load balancing
• Hands-on experience with Cisco networking platforms
• Ability to troubleshoot layer 2 (ARP and MAC address tables as well as LACP and MC-LAG)
• Ability to troubleshoot DNS problems
• Experience with common network cabling
• Kubernetes CNI (Calico, Cilium)
• Cloud & Hybrid Networking
• Experience with hybrid cloud networking including site-to-site VPNs and private connectivity (AWS Direct Connect, GCP Interconnect)
• Understanding of cloud-native networking services (VPC, Transit Gateway, Cloud Router)
• Automation & Infrastructure-as-Code
• Working knowledge of Terraform for network infrastructure provisioning
• Experience with configuration management tools (Ansible, or similar)
• Observability & Operations
• Experience implementing network monitoring and alerting systems
• Understanding of network performance metrics and logging
• Ability to create and maintain runbooks and documentation
• Security
• Experience implementing network security controls and segmentation
• Understanding of firewall management and security policies
• Familiarity with network access control concepts

Preferred skills:

• EVPN
• Experience with IPv6 rollout
• Juniper specific knowledge and experience
• Linux CLI

Job Title: AI Applications Engineer II

Location: Bangalore/ Chennai, India

About the Role

We’re looking for a passionate AI Applications Engineer II to join our growing Enterprise AI Team. In this role, you’ll help manage, support, and optimize our Google Gemini Enterprise agentic AI platform, ensuring it operates securely, efficiently, and at scale across the organization.

You’ll spend most of your time focused on Gemini Enterprise platform administration, governance, and support, along with some dedicated time to enhancing/building/doing POC work on agentic and automation projects that furthers performance, user experience, and integration with Five9 enterprise systems.

If you’re driven by innovation, precision, and the opportunity to shape how AI supports a global business, this is the role for you.

Key Responsibilities

• Administer, configure, and optimize Gemini Enterprise and related AI agentic functionality to ensure seamless performance and compliance within Five9 environments.
• Manage user provisioning, license assignments, access controls, and security policies, ensuring consistency with IT, Infosec and compliance governance standards.
• Oversee appropriate Google Cloud Platform (GCP) resources — including Project services, AI/ML engine, storage, and Gemini AI models — focusing on reliability, performance, and cost management.
• Support cloud run workflows, CI/CD automation pipelines, and containerized environments, leveraging tools such as Terraform, Docker, and Kubernetes.
• Partner with data engineers, DevOps teams, and business stakeholders to troubleshoot issues, implement updates, and ensure timely support for production workloads.
• Conduct prompt engineering and workflow optimization to improve agentic AI accuracy, responsiveness, and relevance.
• Maintain and update documentation, runbooks, and best practice guides for platform operations, deployment, and support.
• Deliver training and enablement sessions to end users and power users on Gemini Enterprise capabilities and AI use cases.
• Continuously evaluate emerging Google AI and Gemini agentic technologies, recommending improvements that enhance scalability and automation.

Key Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field (AI or data systems focus preferred).
• Minimum of 3 years of GCP experience supporting or developing AI/ML solutions on Google platform.
• Hands on experience with AI/ ML solutions/apps and operational best practices (ML Ops experience is advantageous).
• Proficiency with GCP services such as Compute Engine, IAM, Kubernetes, VPC, BQ, etc.
• Experience in automation and scripting using Python, Bash, and Infrastructure as Code (IaC) tools such as Terraform or Deployment Manager.
• Familiarity with Gemini Enterprise or similar enterprise AI frameworks, including prompt engineering, AI agent configuration, and data governance.
• Strong understanding of security, compliance, and auditing practices, including DLP, Access Transparency, and data residency standards.
• Excellent problem-solving, analytical, and troubleshooting skills.
• Strong interpersonal and communication abilities, with the capacity to explain technical topics to non-technical audiences.
• A passion for innovation, continuous learning, and driving impactful AI adoption across the enterprise.

Why You’ll Love Working Here

• Be part of a forward-thinking Enterprise AI Team, driving next-generation innovation across the company.
• Work hands-on with cutting-edge technologies like Google Gemini Enterprise and other agentic AI tools that power real-world business applications.
• Collaborate with skilled engineers, data scientists, and business leaders on high-visibility projects that make a measurable impact.
• Enjoy a culture that values experimentation, continuous learning, and teamwork, with opportunities to grow your skills in cloud operations and AI engineering.
• Play a key role in transforming enterprise workflows through AI innovation, scalability, and operational excellence.

Required:

• 3+ in Windows desktop application development using Windows App SDK, WinUI (or similar), C#, XAML — and ideally additional experience with native Windows code (C++, Win32/WinRT/COM).
• Deep understanding of Windows application architecture, including interop between managed code (.NET) and native code.
• Proven track record of designing, building, and shipping production-quality desktop applications, with an emphasis on reliability, performance, scalability, and maintainability.
• Strong experience with accessibility APIs on Windows (e.g. Microsoft UI Automation or similar), and a dedication to building accessible and inclusive software.
• Excellent software engineering fundamentals: OOP, design patterns, data structures, algorithms, memory management, multi-threading or asynchronous programming (where relevant).
• Experience leading technical design, mentoring other engineers, conducting code reviews, and making architecture-level decisions.
• Strong communication skills; ability to articulate tradeoffs, collaborate with cross-functional teams, and drive consensus.
• A user-centric mindset: focus on building polished, intuitive, and accessible experiences for end users.

Preferred / Bonus:

• Experience with writing automated tests for UI — unit tests, integration tests, UI automation tests; familiarity with relevant testing frameworks.
• Experience with performance optimization for desktop apps (memory usage, startup time, rendering performance, high-DPI support, responsiveness under load).
• Experience with localization/globalization, right-to-left UI support, internationalization, accessibility for multiple regions.
• Familiarity with telemetry, analytics, crash reporting, logging, and error monitoring in desktop applications.
• Previous experience in shaping CI/CD workflows, release pipelines, and deployment strategies for desktop applications.
• Demonstrated ability to take ownership of feature areas or modules and drive them long-term, including maintenance, refactoring, and technical debt management.

What we offer

• A high-impact role: you will define architecture, shape the future of our Windows product, and directly influence what millions of users see and experience.
• A collaborative, flat-structure engineering culture — you are not just a coder, but a builder and a decision-maker.
• Opportunities to lead — mentor others, steer technical direction, and grow into broader technical leadership (e.g. Tech Lead, Architect).
• Flexibility, autonomy, and responsibility: you define how to solve problems, own features end-to-end, and contribute to long-term product vision.
• A purpose-driven mission: building software that’s reliable, accessible, and user-centered — making a real difference for people.                  

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Speechify is committed to a diverse and inclusive workplace. 
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

About the Team At Business Technology, we use Appian to run Appian. We are launching our first internal AI team to build the foundation for how our global company works. This team won't just use AI, they will build the brain of the enterprise, spanning everything from predictive intelligence in our data warehouse to the GenAI infrastructure that powers our internal autonomous agents.

We are hiring a founding group of engineers to kickstart this mission. As an AI Engineer on this team, you won’t be maintaining legacy systems; you’ll be building from the ground up. You will own the full spectrum of AI: crafting predictive ML models to find insights in our data warehouse and architecting GenAI systems that allow any employee to interact with enterprise knowledge through intelligent agents.

If you want to be part of the original team that defines internal AI for a leading automation company, this is your moment.

PLEASE NOTE: This is a midlevel role and is aimed at people with 3+ years experience

What you’ll do:

• Build the AI Platform: Design, deploy, and scale GenAI infrastructure on GCP Vertex AI (preferred) or AWS Bedrock.
• Build & Operate MCP Servers: Develop and maintain Model Context Protocol (MCP) servers that expose enterprise systems (databases, APIs, internal tools) as structured, AI-consumable capabilities.
• Design the Tool Layer: Build the tool registry and invocation framework that allows agents to interact with internal systems safely and reliably including schema design, access controls, and error handling.
• Engineer Agent-to-Agent Infrastructure: Architect the communication and coordination layer that allows specialized agents to delegate tasks, share context, and compose into larger autonomous workflows.
• Own the Retrieval Layer: Architect and operate RAG systems, including vector stores, embedding pipelines, chunking strategies, and retrieval evaluation frameworks.
• Establish AI Reliability: Instrument AI systems with logging, tracing, latency monitoring, and evaluation hooks so agents can be trusted, debugged, and improved in production.

Required Qualifications:

• AI Infrastructure Experience: Professional experience building and deploying production-grade GenAI systems on GCP Vertex AI or AWS Bedrock including LLM APIs, agent frameworks, and RAG pipelines.
• Python Mastery: Deep proficiency in Python and common AI/ML libraries (e.g., LangChain, LlamaIndex, OpenAI SDK, Google Cloud AI SDK).
• Agentic Systems: Hands-on experience building multi-step, tool-calling AI agents that operate reliably in production including tool schema design, structured outputs, and failure handling.
• MCP or Tool Protocol Experience: Familiarity with Model Context Protocol (MCP) or equivalent patterns for exposing enterprise resources to AI systems as callable, permissioned tools.
• Vector & Retrieval Systems: Experience with vector databases (Pinecone, pgvector, or similar) and embedding-based retrieval at scale.
• Technical Foundation: B.S. in Computer Science, Engineering, or a related technical field.
• The Pioneer Mindset: A self-starter who is excited to be part of a "first-of-its-kind" team and thrives in environments where you are building the playbook.

Preferred Qualifications:

• Multi-Agent Architectures: Experience designing orchestrator/subagent patterns, agent handoff protocols, or systems where multiple AI models coordinate to complete complex tasks (e.g., using frameworks like LangGraph, CrewAI, or AutoGen).
• AI Observability: Experience with LLM evaluation frameworks, prompt regression testing, or agent trace monitoring (e.g. custom eval pipelines).
• Data Warehouse Integration: Familiarity with SQL and pulling data from Snowflake or BigQuery to ground AI agents in live business context.
• Appian Exposure: Experience with the Appian platform or interest in integrating AI agents into low-code automation workflows.
• Predictive ML (Nice to Have): Some familiarity with ML fundamentals is a plus, but not a focus of this role.

This role is based at our Chennai office in Brigade World Trade Center Chennai. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian.