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.

Job Description

We’re seeking a hands-on Senior Data Architect to design and modernize scalable, AI-ready data platforms across cloud. The ideal candidate has deep technical expertise in AWS, PySpark, and Python, and experience migrating legacy Java-based scripts to Spark frameworks while ensuring data quality, scalability, and performance.

Key Responsibilities

• Design and implement data architecture and pipelines using PySpark, Python, and AWS services (Glue, EMR, S3, Redshift, Athena).
• Modernize legacy systems by converting Java-based migration or ETL scripts into Spark-based solutions.
• Build and manage data lakes and data warehouses optimized for analytics and AI/ML workflows.
• Collaborate with data scientists and analysts to enable model training, deployment, and continuous data delivery.
• Define and document HLD (High-Level Design) and LLD (Low-Level Design) for scalable data systems.
• Implement standards for data quality, governance, performance optimization, and security.
• Lead troubleshooting, performance tuning, and architecture reviews for data pipelines.

Skills and Experience

• 15+ years of experience in data engineering or architecture, with strong hands-on development background.
• Expert-level proficiency in PySpark, Python, and SQL for data processing and transformation.
• Strong understanding of AWS data ecosystem — including Glue, EMR, S3, Redshift, and Lambda.
• Proven experience migrating or re-engineering Java-based ETL systems into modern Spark environments.
• Solid foundation in data lake, data warehouse, and cloud-native architecture design.
• Experience supporting AI/ML data pipelines and integrating data platforms with ML workflows.
• Strong documentation skills (HLD, LLD) and ability to communicate architecture clearly to technical and business stakeholders.
• Experience with both RDBMS such as Maria DB/MySQL and No-SQL database such MongoDB
• Experience with GIT, Jenkins, & AWS
• Expertise in performance optimization and cost management for cloud environments
• Ability to manage multiple projects and priorities in a fast-paced environment
• AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional

Why we're hiring:

As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects.

Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks. As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks.

As a hands-on technologist with an extensive data engineering background using Databricks, you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration.

What you'll be doing:

• Design, build, test and maintain data pipelines (ELT), according to business and technical requirements.
• Implement secure platforms with data governance in mind.
• Play a key role in automation and building industry leading solutions against architectural best practices.
• Propose technical designs and develop integrations.
• Deliver data migrations between legacy & modern platforms
• Design & deliver data warehousing solutions and key data engineering workstreams for any required solution.
• Support cross-functional teams across the data space.

What you'll need:

Minimum requirements for this role include:

• 3+ years of experience designing and building scalable distributed data pipelines and dimensional data models
• 3+ years of experience in Python and SQL
• Experience using Databricks platform and PySpark is a must.
• Extensive experience of Microsoft Azure data services – Data Factory, ADLS gen2, Event Hubs, Azure SQL, Azure Key Vault
• Ideally experience in the following – Kafka, Delta Lake, Pandas
• A demonstrable understanding of Continuous Integration, Continuous Delivery (CI/CD) and Agile practices, unit & integration tests and development practices using Azure DevOps.
• Fluency in English.
• Exposure to AI & ML technologies is a plus.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

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.

Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.

Living our values every day results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves.

Our Global Voice Team is looking for a committed, experienced Software Engineer II who is passionate about creating high-performing, scalable, and resilient mission-critical services that form the foundation of Five9’s next-generation contact center platform. You will have the opportunity to combine your existing expertise with new learnings, crafting bespoke solutions that serve our customers and partners.

Responsibilities:

• Participate in an Agile Scrum team that practices DevOps.
• Write clean, well-documented code and corresponding tests.
• Deliver your code as part of an overall solution running in the public cloud.
• Develop and enhance our Media Server to support real-time integrations with Large Language Models (LLMs) and other AI services.

Required Skills:

• 3+ years of professional experience in software development, including experience in C and/or C++.
• Hands-on experience developing software for real-time communications signaling and media protocols (e.g., SIP, RTP).
• Ability to methodically troubleshoot complex systems.
• Excellent communication and organizational skills, with a strong sense of ownership.

Technical Skills:

• Modern C++ (C++17+)
• RTP/SIP, audio codecs, SIP/SDP
• ASR/TTS integration
• AI APIs
• Cloud platforms (AWS, Azure, GCP)
• CI/CD
• Containers
• Site Reliability Engineering (SRE) principles
• AI/ML and Large Language Models (LLMs)

Why we're hiring:

As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects.
Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks. As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks.
As a hands-on technologist with an extensive data engineering background using Databricks, you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration.

What you'll be doing:

• Design, build, test and maintain data pipelines (ELT), according to business and technical requirements.
• Implement secure platforms with data governance in mind.
• Play a key role in automation and building industry leading solutions against architectural best practices.
• Propose technical designs and develop integrations.
• Deliver data migrations between legacy & modern platforms
• Design & deliver data warehousing solutions and key data engineering workstreams for any required solution.
• Support cross-functional teams across the data space.

What you'll need:

Minimum requirements for this role include:

• 3+ years of experience designing and building scalable distributed data pipelines and dimensional data models
• 3+ years of experience in Python and SQL
• Experience using Databricks platform and PySpark is a must.
• Extensive experience of Microsoft Azure data services – Data Factory, ADLS gen2, Event Hubs, Azure SQL, Azure Key Vault
• Ideally experience in the following – Kafka, Delta Lake, Pandas
• A demonstrable understanding of Continuous Integration, Continuous Delivery (CI/CD) and Agile practices, unit & integration tests and development practices using Azure DevOps.
• Fluency in English.
• Exposure to AI & ML technologies is a plus.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

Role Overview
We are seeking a Staff Frontend Engineer to be the technical anchor for our frontend capability. This role goes beyond feature delivery — you will define the frontend architecture, establish the component design system, own the Next.js application structure, drive performance standards, and mentor Senior and mid-level frontend engineers. You will build the most complex, data-intensive UI surfaces: real-time attribution dashboards, AI powered campaign builders, and platform-embedded intelligence widgets — all in React + Next.js stack integrated with Elasticsearch-powered search and streaming AI responses.  

Key Responsibilities
• Own and evolve the frontend architecture: Next.js App Router structure, component boundaries, state management strategy (Redux), and data-fetching patterns — applying hexagonal UI principles where the component layer is decoupled from specific backend service contracts.

• Design and build the most technically complex UI surfaces: real-time attribution dashboards (streaming data), AI-powered campaign builder (LLM response streaming), Elasticsearch-backed customer search with faceted filtering, and platform-embedded opportunity cards.

• Define the component design system: atomic component library, theming contracts, accessibility standards (WCAG 2.1), and Storybook-based documentation.

• Establish frontend performance standards: Core Web Vitals targets, bundle size budgets, SSR/SSG strategy with Next.js, lazy loading, and virtualization for large data tables.

• Lead Next.js architecture decisions: App Router vs. Pages Router tradeoffs, RSC (React Server Components) applicability, streaming SSR for AI-generated content, and API route design.

• Integrate AI-native frontend patterns: streaming LLM responses into UI components, real-time score updates from Redis/Aerospike via SSE, and Elasticsearch typeahead search. 

• Drive code quality through design reviews, code reviews, pair programming, and frontend-specific engineering standards.

• Mentor Senior and mid-level frontend engineers — setting the bar for component design, test coverage, and performance discipline.

• Collaborate closely with backend Staff Engineers to define API contracts and with designers to implement pixel-perfect, accessible UIs

Skills & Qualifications

• 8+ years of frontend engineering experience with deep React and Next.js expertise in production systems.

• Mastery of Next.js 14+ App Router, React Server Components, streaming SSR, and static generation — knowing when to apply each pattern.

• Strong TypeScript expertise: type safety across component props, API contracts, Redux store shape, and server/client boundaries.

• Deep Redux expertise: slice design, selector optimization, middleware patterns, and RTK Query for data fetching.

• Proven experience building data-intensive dashboards with real-time data (WebSocket, SSE, or polling) and chart libraries (Recharts, D3.js).

• Experience integrating Elasticsearch-powered search UIs: typeahead, faceted search, and result ranking display.

• Strong frontend performance engineering: bundle analysis, code splitting, memoization, virtualization, and Core Web Vitals optimization.

• Experience establishing and maintaining component design systems with accessibility standards.

• Experience mentoring engineers and raising the technical bar across a frontend team. 

Good to Have

• Experience streaming LLM/AI-generated content into React UI components (token streaming, partial rendering patterns).

• Familiarity with platform-embedded micro-frontend patterns (module federation or iframe-based embedding).

• Background in automotive retail, eCommerce analytics, or SaaS BI/reporting platforms.

• Experience with Storybook for component documentation and visual regression testing. 

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

Job Description

You will develop enterprise-grade frontend experiences embedded within our core platform and collaborate closely with designers, backend engineers, and product managers to deliver a world-class, AI-native user experience. You will build scalable, performant React + Next.js applications that surface real-time intelligence, campaign management interfaces, and data-rich dashboards — deeply integrated with our backend services and platform component framework.

Key Responsibilities
• Design and build responsive, reusable UI components using ReactJS and Next.js — including data visualization dashboards, campaign management interfaces, and customer intelligence widgets.
• Develop large-scale, cloud-ready frontend applications integrated with backend REST APIs, real-time data streams, and Elasticsearch-powered search experiences.
• Manage application state using Redux, ensuring seamless synchronization with backend microservices.
• Build platform-embedded frontend components following the hexagonal UI principle — components are independent, composable, and decoupled from specific data sources via port interfaces.
• Leverage Next.js SSR and SSG capabilities where appropriate for performance-critical views and SEO relevant surfaces.
• Collaborate with product, design, and backend teams to rapidly prototype and deliver high-quality, data-rich features.
• Ensure usability, performance, security, and visual consistency across environments and devices.
• Diagnose and fix UI bugs, rendering performance issues, and frontend bottlenecks.
• Write high-quality, maintainable code with thorough unit and integration tests.
• Follow Tekion UI, design, and engineering best practices.

Skills & Experience
• 3-5 years of experience in frontend engineering; Bachelor's degree in Computer Science or a related field.
• Strong hands-on expertise with React, Next.js, JavaScript/TypeScript, and Redux.
• Solid knowledge of HTML, CSS, and web standards (REST, HTTP, JSON, DOM, W3C).
• Experience building enterprise-grade SaaS applications with real-time data and complex state management requirements.
• Familiarity with Next.js App Router, SSR, SSG, and API routes.
• Excellent understanding of frontend performance: code splitting, lazy loading, memoization, virtualization.
• Experience with Git and project management tools (e.g., JIRA).
• Proven experience delivering scalable, high-performance frontend systems with thorough test coverage.
• Strong sense of ownership and bias for action in a fast-paced startup environment.

Preferred Skills
• Experience integrating AI-generated content and LLM-streamed responses into frontend components.
• Familiarity with data visualization libraries (Recharts, D3.js) for analytics and reporting dashboards.
• Experience building embedded micro-frontend components within larger platform shells.
• Exposure to Elasticsearch-powered search UI patterns (faceted search, typeahead, result ranking).

Perks & Benefits
• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Role Overview:

We are looking for a hands-on Product Architect / Engineer to design and build an AI-driven operations platform focused on intelligent automation, insights, and optimization across cloud, network, and application operations.This role blends product thinking, architecture, and deep engineering across AI/ML and Agentic AI systems.

Key Responsibilities:

• Architect and build the agentic AI platform leveraging AI, ML, and Agentic AI frameworks
• Design multi-agent systems for use cases for operations domains like Cloud Ops, NetworkOps, ServiceDesk, root cause analysis, anomaly detection, and predictive insights
• Develop data pipelines and telemetry fabric for ingesting and processing large-scale operational data (logs, metrics, traces, topology)
• Build and integrate LLM-powered copilots and autonomous agents for operations 
• Define product architecture, including microservices, APIs, event-driven systems, and scalable cloud-native patterns
• Translate business needs into AI-driven product features and accelerators
• Collaborate with product, operations, and engineering teams to deliver end-to-end capabilities

Key Skills:

• Strong experience in product architecture and full-stack engineering
• Hands-on expertise in:
• AI/ML (model development, inference, MLOps)
• LLMs and Agentic AI frameworks (multi-agent orchestration, reasoning systems)
• Data engineering (streaming, batch, real-time analytics)
• Proficiency in Python and modern frameworks
• Experience with cloud platforms (AWS, Azure) and cloud-native architecture
• Agent framework experience – Microsoft agent framework, langgraph and langchain.
• Strong understanding of:
• Observability systems (logs, metrics, traces)
• AIOps / IT operations platforms
• API design and microservices architecture
• Familiarity with vector databases, embeddings, RAG architectures, and knowledge graphs

Good to Have:

• Experience building autonomous AI agents for IT/network/application operations
• Exposure to FinOps, Cloud Cost Optimization,
• Knowledge of network topology, infrastructure ops, or ITSM tools
• Experience with real-time decisioning systems and event correlation engines

Job Description
You will develop enterprise-grade frontend experiences embedded within our core platform and collaborate closely with designers, backend engineers, and product managers to deliver a world-class, AI-native user experience. You will build scalable, performant React + Next.js applications that surface real-time intelligence, campaign management interfaces, and data-rich dashboards — deeply integrated with our backend services and platform component framework.

Key Responsibilities
• Design and build responsive, reusable UI components using ReactJS and Next.js — including data visualization dashboards, campaign management interfaces, and customer intelligence widgets.
• Develop large-scale, cloud-ready frontend applications integrated with backend REST APIs, real-time data streams, and Elasticsearch-powered search experiences.
• Manage application state using Redux, ensuring seamless synchronization with backend microservices.
• Build platform-embedded frontend components following the hexagonal UI principle — components are independent, composable, and decoupled from specific data sources via port interfaces.
• Leverage Next.js SSR and SSG capabilities where appropriate for performance-critical views and SEO relevant surfaces.
• Collaborate with product, design, and backend teams to rapidly prototype and deliver high-quality, data-rich features.
• Ensure usability, performance, security, and visual consistency across environments and devices.
• Diagnose and fix UI bugs, rendering performance issues, and frontend bottlenecks.
• Write high-quality, maintainable code with thorough unit and integration tests.
• Follow Tekion UI, design, and engineering best practices.

Skills & Experience
• 5+ years of experience in frontend engineering; Bachelor's degree in Computer Science or a related field.
• Strong hands-on expertise with React, Next.js, JavaScript/TypeScript, and Redux.
• Solid knowledge of HTML, CSS, and web standards (REST, HTTP, JSON, DOM, W3C).
• Experience building enterprise-grade SaaS applications with real-time data and complex state management requirements.
• Familiarity with Next.js App Router, SSR, SSG, and API routes.
• Excellent understanding of frontend performance: code splitting, lazy loading, memoization, virtualization.
• Experience with Git and project management tools (e.g., JIRA).
• Proven experience delivering scalable, high-performance frontend systems with thorough test coverage.
• Strong sense of ownership and bias for action in a fast-paced startup environment.

Preferred Skills
• Experience integrating AI-generated content and LLM-streamed responses into frontend components.
• Familiarity with data visualization libraries (Recharts, D3.js) for analytics and reporting dashboards.
• Experience building embedded micro-frontend components within larger platform shells.
• Exposure to Elasticsearch-powered search UI patterns (faceted search, typeahead, result ranking).

Perks & Benefits
• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

The Role

We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.

This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.

What You Will Do

• Build & Deploy (60%):

Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.

Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.

Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.

Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.

• Customer Engineering (40%):

Serve as the technical face of the company for our most demanding accounts.

Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.

Translate technical constraints into business value for non-technical executives.

Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.

The "Must-Haves"

• Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
• Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
• Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
• Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).

The "Why You" (Soft Skills)

• Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
• Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
• Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.

What will set you apart

• Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.

Tech Stack

• Languages: Python (Expert).
• AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
• Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

Role Overview

As the most senior Individual Contributor (IC) in our Chennai office, you will serve as the site’s Technical North Star and strategic engineering partner. Reporting directly to the VP of Engineering, you are the steward of our technical excellence, responsible for defining high-level architectural direction and maintaining a world-class engineering bar across all local domains.

This is a force multiplier role. You are not just a lead developer; you are the person who ensures our regional engineering efforts align with global business goals. You will provide the technical cohesion necessary to build scalable, secure, and and operationally elite systems while mentoring the next generation of high-level individual contributors.

Key Responsibilities

• Architectural Stewardship: Own the high-level technical roadmap for the Chennai site. Lead the transition of core engines and large-scale monoliths into modern, distributed, cloud-native ecosystems.

• Engineering Standards: Drive site-wide quality through rigorous design reviews and the establishment of technical tenets that prioritize long-term system health over short-term delivery.

• AI-First Evolution: Design and implement automation-led architectures and AI-integrated workflows to enhance both engineering velocity and product intelligence.

• Principal Mentorship: Act as the primary mentor for Staff and Principal-level ICs, guiding them through complex system trade-offs and career growth toward organizational leadership.

• Strategic Advisory: Partner with the VP of Engineering to identify technical risks, bridge platform gaps, and ensure the Chennai office operates as a global center of innovation.

• Cross-Domain Cohesion: Facilitate technical councils and RFC processes to ensure architectural consistency and knowledge sharing across disparate product teams.

Required Experience & Skills

• 15+ Years of Systems Engineering: A deep history of designing, deploying, and maintaining high-traffic, large-scale software systems.

• Organizational Influence: Proven ability to shift the technical trajectory of multiple teams or business units without direct reporting authority.

• Architectural Mastery: Expert-level knowledge of distributed systems, cloud-native patterns, and microservices at global scale.

• Systems Thinking: An "automation-first" mindset with experience integrating AI/ML or advanced CI/CD into the core development lifecycle.

• Data-Driven Leadership: Ability to drive consensus among senior stakeholders using objective architectural principles and technical merit.

Preferred Qualifications

• Global Scale Experience: Previous experience operating at a Staff+ or Principal level within a global engineering organization, impacting multi-region infrastructures.

• Modernization Track Record: Demonstrated success in re-architecting legacy core engines into high-performance, modular platforms.

• Technical Community Leader: Experience building internal engineering cultures, from hosting deep-dive sessions to formalizing site-wide RFC standards.

Responsibilities

We are looking for an experienced Senior Forward Deployed Engineer to join our AI Solutions team. In this role, you will be responsible for designing, developing, and deploying advanced AI Agentic Solutions that exhibit autonomous, proactive, and adaptive behaviors. This role requires a deep understanding of AI/ML technologies, integration, automation experience and solution architecture, combined with strong problem-solving skills and the ability to collaborate across multidisciplinary teams.

• Architect and implement agent-based AI solutions using the Workato Agentic AI platform.

• Designing intelligent, autonomous, and efficient agentic AI workflows that utilize multi-agent collaboration, orchestration, and the automation capabilities provided by the Workato platform.

• Design and deploy Retrieval-Augmented Generation (RAG) systems using Workato’s Agentic AI capabilities, leveraging its connectors, workflows, and recipes to enable context-aware, grounded, and real-time responses from large language models (LLMs).

• Develop advanced prompting, memory management, and behavior-planning techniques to enable LLMs and agents to reliably author and execute complex workflows.

• Act as a technical solutions expert with a strong aptitude in troubleshooting and analyzing AI-driven architectures, including scalable RAG pipelines and agent frameworks built using the Workato Agentic AI platform.

• Develop and maintain robust, scalable AI-powered IT workflows with agent-based decision-making, dynamic retrieval mechanisms, and seamless integration using the Workato Agentic AI platform.

• Continuously monitor and improve AI system performance, ensuring efficiency and reliability.

• Work closely with customers to understand use cases and deliver tailored, scalable agentic AI and RAG-based solutions using the Workato Agentic AI platform, while prioritizing exceptional customer service to ensure alignment with both technical and business needs, as well as satisfaction and successful implementation.

• Collaborate with cross-functional teams to integrate AI workflows into existing IT frameworks, ensuring smooth and seamless deployment.

• Contribute to internal process improvements and promote knowledge sharing by adding to Workato’s knowledge base.

• Play an instrumental role in all phases of product development, from ideation to implementation, contributing valuable insights and expertise.

• Assist the product manager in creating technical and design specifications, ensuring alignment with product goals and user needs.

• Leverage strong communication skills to effectively translate complex technical concepts into accessible insights for non-technical audiences.

Requirements

Please note: In this role, you will be supporting the US business hours from 6:30 PM to 3:30 AM IST!

Qualifications / Experience / Technical Skills

• BTech/BE or higher technical education in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

• A total of 8+ years of relevant experience in design, development, and implementation, with at least 3 years of experience with the Workato platform, is a must.

• Proven experience in AI engineering, with a focus on agent-based systems.

• Demonstrated ability to design and implement scalable AI-driven workflows that enhance IT operations.

• Knowledge of implementing integration projects is essential. Hands-on experience with automation technologies, middleware, integration architecture patterns, web services technologies, enterprise messaging patterns, APIs, SOA, ESB, BPM, SDKs, and databases.

• 5+ years of experience working with integration platforms such as Workato, TIBCO, Dell Boomi, MuleSoft, or other integration/automation tools is a plus. Experience with cloud technologies—iPaaS, SaaS applications, and cloud infrastructure—is also a plus.

• Strong working knowledge of APIs—RESTful, SOAP/XML. Solid understanding of data structures—JSON. Sound knowledge of any RDBMS/NoSQL.

• 2-3 years of coding experience (Java/Python/Ruby).

• Technical background or a solid understanding of technology and industry trends, especially in the app integration space.

• Experience working with cloud business apps like Workday, NetSuite, Salesforce, ServiceNow, Marketo is a plus.

• Working knowledge of Microservices or API-based integration architecture, event-driven architecture, and process automation via BPM or RPA is a plus.

Soft Skills / Personal Characteristics

• Strong collaboration skills, ability to adapt to a dynamic start-up environment, with a passion for making an impact.

• Strong critical thinking, analytical skills with an entrepreneurial and proactive mindset.

• Ability to effectively prioritize tasks and manage time, even under high-pressure situations.

• Strong written and oral communication skills in English, with the ability to convey complex technical concepts effectively to a non-technical audience.

• Fast learner who can independently conduct extensive research and synthesize ideas, information and options quickly.

• Be proactive about solving problems and be ready to take on additional initiatives and responsibilities as they emerge.

Please respond to the Job Application Questions below with thorough and honest answers - concise yet detailed responses will distinguish you in our selection process. 
All submissions are personally reviewed by the Hiring Team, not evaluated by AI.

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.  

Who we seek:

We’re looking for a Senior Software Engineer with a "can do anything" spirit for our Engineering team in Chennai. Working on security & governance applications developing advanced security & governance oriented integrations and applications which brings precise and targeted value to our customers. As a senior software engineer, you will be responsible for building new services and products from scratch and bringing innovation to the team's developments. Our ideal candidate is a team player who has strong hands-on full stack experience and is capable of claiming ownership of a feature, from one end to another.

What you’ll do:

• Design, develop, and test high-quality code, ensuring comprehensive coverage with unit, integration, and End-to-End (E2E) tests.
• Develop robust Backend SDKs and the company’s next-generation SaaS products.
• Lead code reviews, enforce coding best practices, and maintain rigorous software development standards, especially concerning data handling.
• Troubleshoot and resolve complex system issues promptly to ensure maximum uptime and system reliability.
• Drive and influence key technological and architectural decisions for the team.
• Mentor and guide fellow team members through reviewing their design and code.
• Own and complete tasks end-to-end, actively participating in the Agile Scrum process.

What you’ll bring:

• Minimum of 5 years of hands-on experience developing Java Microservices.
• Proven ability to manage and scale high-volume engineering solutions.
• Deep understanding of CI/CD principles and experience working with external and in-house APIs and SDKs.
• Experience leveraging AI Development Tools (e.g., GitHub Copilot, Cursor) as a "Peer Programmer" to boost productivity.
• Strong analytical skills and excellent problem-solving abilities.
• Experience in automation testing.
• Excellent communication skills and a collaborative, "can-do" mindset for working with cross-functional teams to ensure end-to-end quality.

Advantages:

• Familiarity with containerization technologies (Docker, Kubernetes).
• Experience with the AWS cloud platform.
• Working knowledge of NoSQL databases and messaging systems (e.g., MongoDB, Elastic, Kafka, Redis).
• Proven experience with the React.js framework.

What’s in it for you?!

Our people are the foundation of our success, and we prioritize offering a wide range of benefits that make our team happier and healthier.

•    Equity participation - everyone shares in our success
•    Hybrid work 
•    Opportunities for professional growth
•    Team fun & company outings
•    Statutory benefits and leave benefits
•    Health Insurance coverage 

Our Values:

We look for people who embody our values - Care, Do, Try & Shine.

• Care - We care about our customers and each other
• Do - We do what it takes to make a positive impact
• Try- We try our best and we don’t give up
• Shine- We shine and make it our mission to always stand out

#LI-HYBRID

#LI-EV2

Why we're hiring:

The Automation Engineer is responsible for designing, developing, and maintaining security automation solutions that enhance detection, response, workflow efficiency, and operational consistency across Operational Security. Working under the Automation Lead, this role builds high-quality SOAR playbooks, integrations, scripts, AI-assisted workflows, and orchestration pipelines to reduce manual workloads and support the Autonomic Security Operations (ASO) model.

What you'll be doing:

Core Responsibilities

Automation Engineering & Development

• Develop SOAR playbooks, workflows, and automations for alert triage, enrichment, containment, and remediation.
• Build scalable, reusable automation components, scripts, and integrations.
• Implement high-quality scripting using Python, PowerShell, and REST APIs.
• Ensure appropriate version control, QA, testing, and documentation of automation artefacts.
• Maintain reliability of automations by monitoring performance, exceptions, and system behaviour.

Platform Integration & Tooling Engineering

• Integrate SOAR with SIEM, EDR, TIP, cloud-native security tools, and case management systems.
• Engineer automation pipelines to support Microsoft and Google security ecosystems.
• Develop API integrations, webhooks, and event-driven automation triggers.
• Support data transformation, enrichment, and telemetry orchestration requirements.

AI / ML Automation Enablement

• Contribute to embedding AI/ML-driven enrichment and correlation logic into automated workflows.
• Support operationalisation of ML models for anomaly detection and decision support.
• Collaborate with data and detection teams to refine and enhance AI-enabled automation.

Workflow Engineering & Process Automation

• Translate SOPs, response runbooks, and detection workflows into automated processes.
• Identify automation opportunities to eliminate manual tasks across SecOps functions.
• Ensure automated processes remain consistent, auditable, and compliant with Operational Security standards.

Operational Collaboration & Support

• Work with Detection Engineering, Incident Response, Threat Hunting, and Threat Intelligence teams to automate use cases.
• Participate in post-incident reviews and embed improvements into automation workflows.
• Assist with tool evaluations, optimisation initiatives, and integration efforts led by the Automation Lead.

Continuous Improvement

• Contribute to a backlog of automation enhancements and new capabilities.
• Optimise accuracy, resilience, and efficiency across automation workflows.
• Ensure alignment with GCAT SOC10x principles, including 10X Technology, Process, Speed, and Visibility.

What you'll need:

Technical Expertise

• Experience with SOAR platforms such as Cortex XSOAR, Splunk SOAR, or Chronicle SOAR.
• Proficiency in Python and/or PowerShell for automation development.
• Strong understanding of REST APIs, JSON, and event-driven automation.
• Experience integrating SIEM, EDR, TIP, and cloud-native security tools.

Process & Operational Knowledge

• Understanding of workflows across SOC, Incident Response, Threat Hunting, and Detection Engineering.
• Ability to convert operational requirements and SOPs into engineered automation.
• Familiarity with playbooks, runbooks, and security process governance.

Collaboration & Delivery

• Strong communication and documentation skills.
• Ability to work in an engineering-led, automation-first culture.
• Experience working with cross-functional technical teams in security operations.

Certifications (Preferred)

• SOAR platform certifications.
• GIAC (GMON, GCTI, GCIH, GCDA).
• Python or scripting certifications.
• Azure or GCP cloud certifications.

Key Attributes

• Engineering-first mindset with strong attention to detail.
• Problem-solving orientation with a focus on automation and efficiency.
• Structured, methodical, and reliable approach to delivery.
• Commitment to operational excellence and continuous improvement.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

#LI-Hybrid 

Role Overview

We are looking for a Senior Backend Engineer to design, build, and scale robust backend services that power complex business workflows. This role requires strong ownership, deep Java expertise, a solid grounding in hexagonal architecture, and the ability to collaborate effectively across product, QA, AI/ML, and engineering teams in a fast-moving, AI-native environment.

Key Responsibilities

• Design and build Java (Spring Boot 3.x) microservices following hexagonal architecture — clean domain logic isolated from MongoDB, PostgreSQL, Cosmos DB, and Kafka adapter implementations.

• Develop and maintain REST APIs, Kafka event consumers/producers, and domain service logic for campaign, scoring, attribution, and customer profile workflows.

• Build and manage MongoDB document schemas and PostgreSQL relational schemas for high-throughput, multi-tenant use cases. 

• Implement Cosmos DB data models for event and state storage with appropriate partition key and consistency strategies.

• Take end-to-end ownership of components — from domain design and hexagonal adapter implementation through deployment and ongoing optimization.

• Integrate with Elasticsearch for campaign search, customer lookup, and full-text query workloads.

• Configure and tune Redis or Aerospike for frequency cap enforcement, scoring cache, and session state management.

• Identify and resolve performance bottlenecks across services, event pipelines, and data layers.

• Participate actively in design discussions, architecture decisions, and code reviews.

• Mentor Junior engineers and act as a role model for code quality, hexagonal design, and AI-native engineering best practices.

Skills & Qualifications

• 5+ years of backend engineering experience; Bachelor's or Master's degree in Computer Science or a related field.

• Strong Java 21 and Spring Boot 3.x expertise; solid grasp of hexagonal architecture and clean domain modeling.

• Experience with Kafka: consumer/producer patterns, at-least-once delivery, idempotent processing, and event-driven service design.

• Hands-on MongoDB experience: document schema design, indexing, aggregation pipelines, multi-tenant isolation.

• PostgreSQL experience: schema design, query optimization, migration management.

• Familiarity with Cosmos DB or equivalent distributed key-value / document stores.

• Experience with Elasticsearch for search and analytics workloads.

• Experience with Redis or Aerospike for high-throughput caching patterns.

• Familiarity with cloud-based systems on AWS (EKS, MSK, S3).

• Strong debugging, performance tuning, and system optimization skills.

• Familiarity with Agile/Scrum development practices and CI/CD pipelines.

Good to Have

• Experience with Temporal for workflow orchestration.

• Familiarity with AI-native integration patterns: MCP tool registration, scoring API contracts, LLM gateway usage.

• Working knowledge of Python for understanding AI/ML service outputs and integrating scoring results.

• Background in enterprise-scale SaaS platforms: eCommerce, supply chain, or similar. 

Job Description

We are looking for a Software Engineer II to join one of our Scrum teams building AI-native, event-driven services for automotive retail intelligence. This is a core contributor role for engineers with 2–4 years of experience who are ready to take end-to-end ownership of features, grow their distributed systems skills, and work in a high velocity environment that demands code quality, hexagonal architecture discipline, and genuine curiosity about AI-native engineering.

Key Responsibilities

• Develop and maintain Java (Spring Boot 3.x) backend services — implementing domain logic, REST APIs, Kafka event consumers/producers, and MongoDB/PostgreSQL persistence adapters following hexagonal architecture patterns.
• Build features across the full backend slice: domain model, port interface, adapter implementation, unit tests, and integration tests.
• Write integration tests using Testcontainers for MongoDB, PostgreSQL, Kafka, and Elasticsearch adapters — ensuring each adapter is tested independently from the domain core.
• Participate in design discussions, architecture reviews, and code reviews — actively learning from Staff and Senior engineers.
• Investigate and resolve bugs, performance issues, and Kafka consumer lag across services.
• Write clean, well-documented, testable code with consistent application of hexagonal design principles.
• Contribute to golden dataset test scenario design under the guidance of the Product Manager and SDET.
• Operate with ownership and curiosity in a fast-paced, startup environment.

Skills and Experience

• 2–4 years of backend engineering experience; Bachelor's or Master's degree in Computer Science or a related field.
• Solid Java fundamentals: object-oriented design, Spring Boot, REST API implementation, and unit testing (JUnit 5).
• Working knowledge of at least one of: MongoDB, PostgreSQL, or Kafka — with willingness to develop depth across all three.
• Understanding of hexagonal architecture concepts (ports & adapters) — ability to implement adapters under the guidance of senior engineers.
• Familiarity with cloud environments (AWS), containerization (Docker), and CI/CD pipelines.
• Strong problem-solving skills, attention to code quality, and ability to receive and apply feedback quickly.
• Collaborative mindset and clear communication — comfortable asking questions and flagging blockers early.

Preferred Skills

• Exposure to Kafka producers and consumers in a production or learning context.
• Familiarity with Elasticsearch for search and analytics use cases.
• Curiosity about AI/ML systems — awareness of what scoring models, embeddings, and LLMs do at a systems level.
• Exposure to Redis or Aerospike for caching patterns.
  
  

Perks and Benefits

• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Job Description

We are seeking a Staff Backend Engineer to design and build scalable, AI-native backend services that power customer intelligence, campaign orchestration, and attribution at automotive retail scale. This role is the critical technical anchor — defining hexagonal architecture patterns, owning service boundaries, driving AI integration patterns, and setting the engineering bar for the entire team.

Key Responsibilities

 • Architect Java (Spring Boot 3.x) microservices using hexagonal architecture — defining clean domain cores, port interfaces for persistence (MongoDB, PostgreSQL, Cosmos DB), and adapter implementations for Kafka, Elasticsearch, Redis/Aerospike, and external APIs.

• Own core domain models and service boundaries end-to-end: from initial hexagonal design through production operation, Kafka event contracts, and iterative enhancement.

• Build scalable, secure REST APIs and robust Kafka-based event-driven pipelines that consume and produce events across multiple source systems. 

• Design MongoDB document schemas and PostgreSQL relational schemas for high-throughput, multi-tenant workloads — with deep attention to indexing strategy, TTL, and tenant isolation patterns.

• Design Cosmos DB data models for high-throughput event and state storage — partition key strategy, consistency levels, and TTL configuration. 

• Design and implement durable campaign execution workflows using Temporal. 

• Establish and own AI-native integration patterns: MCP tool registration, scoring model serving contracts, LLM gateway integration, and agentic workflow design.

• Identify and resolve performance bottlenecks across services, Kafka pipelines, data layers, and Elasticsearch query performance. 

• Ensure all systems meet reliability, scalability, and observability standards.

• Mentor senior, mid-level, and junior engineers — setting and consistently raising the engineering bar.

Skills & Qualifications

• 8+ years of backend engineering experience with a strong track record delivering production-grade Java systems.

• Deep expertise in hexagonal architecture (ports & adapters) — proven ability to design domain cores fully decoupled from infrastructure layers.

• Strong Java 21 and Spring Boot 3.x expertise with event-driven, microservices-first design. 

• Strong experience with Kafka — consumer groups, partition design, offset management, idempotent consumers, and event-driven service integration.

• Proven experience with MongoDB: document schema design, indexing, aggregation pipelines, and multi tenant isolation patterns.

• Strong PostgreSQL experience: complex schema design, query optimization, migration management.

• Experience with Cosmos DB or equivalent globally distributed key-value stores: partition key design, consistency tuning, high-throughput read/write patterns.

• Solid experience with Elasticsearch: index design, search query optimization, relevance tuning.

• Experience with Redis or Aerospike for high-throughput caching and session/state management.

• Strong understanding of distributed systems: service boundaries, data consistency, idempotency, retries, and circuit breaking on AWS (EKS, MSK).

Preferred Skills

• Experience with Temporal for durable workflow orchestration. 

• Familiarity with MCP tool registration patterns and agentic platform integration.

• Working knowledge of Python for AI/ML pipeline integration (scoring models, feature serving, LLM gateway patterns).

• Prior experience building data platforms, real-time analytics systems, or AI-native SaaS products.

Perks & Benefits 

• Competitive compensation and generous stock options.

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

As a Senior Software Engineer specialising in SAP S/4HANA ABAP/FIORI/AI, you will be a key member of the SAP technical team responsible for designing, developing, and implementing SAP solutions to support business operations. Your primary focus will be on SAP AI developments, UI/UX development using SAP Fiori/UI5,  as well as backend ABAP development for custom solutions and enhancements. You will work closely with functional teams to translate business requirements into technical specifications and ensure seamless integration across SAP modules. Additionally, you will be responsible for maintaining best practices, optimizing performance, and driving innovation through new SAP technologies. You should also have knowledge of emerging AI technologies such as SAP Joule, Robotic Process Automation (RPA) with AI,  AI-powered chatbots and virtual assistants etc. Additionally, you should be familiar with other programming languages like Python or Java and be prepared to conduct Proof of Concepts (POCs) to explore innovative solutions.

What You'll do:

• Build and deliver solutions for integration of AI capabilities for ABAP to accelerate Custom Code Management.
• Design, develop, and implement SAP Fiori/UI5 applications and ABAP backend solutions to meet business requirements.
• Build AI solutions using SAP Joule, MicroApps, agentic AI development
• Collaborate with functional and technical teams to define, develop, and enhance SAP UX and backend solutions.
• Develop and optimize CDS Views, OData Services, and AMDP-based data models for performance efficiency.
• Customize and configure SAP Fiori Launchpad, design intuitive UI/UX interfaces, and ensure responsive applications.
• Develop and maintain SAP workflows, enhancements, and reports using ABAP and RAP.
• Conduct code reviews, performance tuning, and implement best practices in SAP development.
• Provide technical guidance, mentor junior developers, and participate in design workshops.
• Stay updated with SAP’s latest technologies, including SAP BTP, AI/ML integration, and automation tools.
• Troubleshoot and resolve production issues, ensuring smooth system performance and user experience.
• Conduct Proof of Concepts (POCs) to evaluate new technologies and solutions for business applications.
• Build automation scripts using different automation tools like Playwright.

What you bring:

• Bachelor's Degree in Information Technology, Computer Science, Engineering, or related field.
• Minimum 10+ years of professional experience in SAP ABAP development, including at least 5+ years in SAP S/4HANA.
• Minimum 4+ years of experience in SAP Fiori/UI5 development for SAP S/4HANA.
• Minimum 2+ years of working experience as software developer in AI focused cloud application development.
• Good Experience in REST/oData API creation and consumption is beneficial
• Strong expertise in OData services, SAP Gateway, and SAP Business Application Studio.
• Experience in integration with SAP modules such as FI, BRIM, RAR
• Expertise in SAP BTP, cloud-based development, and integration capabilities.
• Familiarity with agent frameworks (ReAct) and CI/CD tools (JIRA, Git, Jenkins).
• Proficiency in Python and experience with AI frameworks.
• Proven track record in building, fine-tuning, and deploying Large Language Models, LangChain, LangGraph, and related GenAI technologies.
• Exposure to Solution Manager, Change Management (CHARM)/CALM, and Focused Build is a plus.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work in an Agile environment and collaborate with global teams.
• Certification in SAP S/4HANA, SAP Fiori/UI5 development, or SAP BTP is an added advantage.

Mandatory Skills:

•   SAP ABAP Development:
•   Strong experience in ABAP development, including Object-Oriented ABAP (OOABAP), BADI, BAPI, ALV, IDOCs, and Enhancements.
•   Expertise in developing CDS Views, AMDP, and using RAP for Fiori applications.
•   SAP FIORI/UI5 Development:
•   Strong hands-on experience with SAP UI5, JavaScript, CSS, HTML5, and jQuery.
•   Experience in SAP Business Application Studio and Web IDE.
•   Proficiency in Fiori Design patterns, UX principles, and Theme Designer.
•   Expertise in Fiori Launchpad configuration and customization.
•   SAP Gateway and OData Services:
•   Strong knowledge of SAP OData framework and troubleshooting SAP custom/standard OData services.
•   Experience in CDS-based OData services and annotations.
•   Deep understanding of MVC architecture.
•   Integration and Performance Optimization:
•   Experience with RESTful APIs, SOAP, and SAP integration technologies.
•   Strong expertise in SAP BTP, Joule, CAP, and Mobile Development Kit (MDK).
•   Experience in performance tuning of UI5 applications and backend queries.
•   Additional Skills:
•   Knowledge of Python, Java, and AI technologies(Joule, MicroApps, Agentic AI) for SAP-related innovations.
•   Expertise in SAP BTP for cloud-based solutions, integration, and extensibility.
•   Experience in conducting Proof of Concepts (POCs) to explore and validate new technological solutions.

#LI-VG1

#LI-Hybrid

Summary: As a Principal Software Engineer at Appian, you will be the primary technical strategist, responsible for shaping the architectural foundation of our platform. Your role involves anticipating future challenges and implementing innovative solutions today. You will drive complex cross-functional initiatives, ensuring Appian remains a leader in the low-code and automation industry.

Responsibilities:

• Define the long-term architectural vision and governance for the Appian platform.
• Identify systemic technical risks and lead task forces to resolve architectural bottlenecks.
• Develop internal tools and SDKs to simplify infrastructure and enhance developer productivity.
• Conduct deep-dive troubleshooting for complex production issues.
• Promote AI-native engineering practices and integrate AI features into the platform.
• Lead the development of core platform libraries and high-risk prototypes.
• Participate in the Architectural Guild and review high-impact design documents.
• Mentor lead and senior engineers, and represent Appian in the tech community.
• Ensure operational resilience with self-healing and highly available systems.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• 15+ years of software engineering experience, with significant experience in architecting large-scale distributed systems.
• Strong understanding of data structures, algorithms, and design patterns.
• Proven transformational leadership in technological migrations or strategies.
• Expertise in Java and Cloud-Native ecosystems.
• Experience with AI/ML at scale and managing AWS multi-region deployments.
• Expert-level proficiency in Java or similar languages.
• Hands-on experience with Docker, Kubernetes, and CI/CD automation.
• Knowledge of high-performance SQL, NoSQL, and Vector Databases.
• Understanding of enterprise-grade security and compliance.

Soft Skills:

• Ability to influence without authority and gain buy-in for technical shifts.
• Business acumen to connect technical decisions to financial outcomes.
• Skilled in navigating complex technical debates and consensus building.
• Passion for building a thriving engineering organization.

About Zuora

At Zuora, we help businesses grow smarter and adapt faster. Our platform powers modern business models — from subscriptions and usage-based pricing to AI-driven and outcome-based offerings — helping companies launch new products, automate complex billing, and unlock predictable, recurring revenue.

We’ve led the Subscription Economy for more than a decade. Now we’re evolving again by building the definitive platform for quote to cash and helping companies monetize their products and services with an adaptable, AI-ready foundation.

The Opportunity

We’re hiring a Senior Site Reliability Engineer to lead reliability strategy and drive AI-powered automation at scale. This role involves owning complex systems, shaping architecture, and influencing cross-functional teams.

You’ll:

• Define and evolve SLOs, SLIs, and resilience patterns
• Build AI-driven automation for detection, remediation, and forecasting
• Lead cloud infrastructure and Kubernetes platforms
• Drive incident response and operational excellence
• Mentor engineers and influence org-wide reliability practices

About You

• 8+ years of hands-on experience in Site Reliability Engineering, DevOps, or large-scale production operations.
• Advanced expertise in AWS, including architecture design across services such as EC2, EKS, VPC, IAM, RDS, S3, and CloudWatch.
• Deep experience with Infrastructure-as-Code using Terraform, including complex modules, state management, and governance.
• Strong programming and automation skills using Python and Shell; experience building production-grade automation systems.
• Expert-level Linux systems knowledge, including performance tuning, security hardening, and deep troubleshooting.
• Proven experience operating distributed systems and data streaming platforms such as Kafka in high-throughput environments.
• Demonstrated ability to work independently on complex, ambiguous problems with broad organizational impact.
• Proven technical leadership experience driving large, cross-team reliability or infrastructure initiatives, including setting technical direction, influencing design decisions, and mentoring engineers to deliver measurable outcomes at scale.

AI & Automation Expertise

• Practical experience designing or implementing AI/ML-driven automation in operations, reliability, or platform engineering.
• Experience integrating AI capabilities into monitoring, alerting, incident response, or workflow automation systems.
• Strong understanding of how AI can be safely and effectively applied in production environments.

Nice to haves:

• Experience with advanced observability platforms (Prometheus, Grafana, ELK, or similar) enhanced with AI-driven insights.
• Familiarity with predictive analytics, anomaly detection, or AIOps platforms.
• Experience influencing architectural decisions at a platform or product level.
• Prior experience operating in a 24/7, global, high-availability SaaS environment.

The Team

Zuora's Cloud Engineering team ensures the reliability, scalability, and operational excellence of global SaaS platforms, operating 24x7 with a follow-the-sun model. The team collaborates closely with Engineering, Security,Product, and Support, leveraging technologies like AWS,Kubernetes, Kafka,Terraform, and Python, with a strong focus on AI-driven operations and automation.

Benefits

Zuora offers a comprehensive total rewards package designed to support ZEOs’ wellbeing, growth, and flexibility. While specific offerings may vary by country, we typically provide:

• Competitive compensation, variable bonus and performance-based reward opportunities, and retirement programs
• Medical, dental, and vision insurance
• Generous, flexible time off, plus paid holidays, wellness days, and a company-wide year-end break
• Paid parental leave (including fully paid leave for eligible ZEOs, subject to local policy)
• Learning & development stipend to support ongoing growth
• Opportunities to volunteer and give back, including charitable donation matching where available
• Mental wellbeing resources and support

*Benefits may vary by location; details will be shared during the interview process

#ZEOLife at Zuora

ZEOs (our employees) are empowered to take ownership, challenge the status quo, and make a real impact. We:

• Collaborate deeply across teams and regions
• Learn constantly and iterate often
• Build an inclusive, high-performance culture where people feel inspired, connected, and valued

Our Commitment to an Inclusive Workplace

Think, be and do you.
At Zuora, different perspectives, experiences, and contributions matter — everyone counts.

Zuora is proud to be an Equal Opportunity Employer committed to creating an inclusive environment for all. We do not discriminate on the basis of, and consider individuals seeking employment with Zuora without regard to, race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance@zuora.com (or local equivalent, where applicable).

Role Overview

We are seeking a Staff Technical Program Manager to own the cross-team delivery machinery for a 20-person AI native engineering organization. This is not a project coordination role — it is a technical program ownership role.  You will maintain the master delivery plan across two Scrum teams and shared resources, track and resolve  
cross-team dependencies (platform teams, ARC backend, OEM integrations), manage risk before it becomes a miss, and create the delivery transparency that allows Engineering, Product, and Executive leadership to make fast, informed decisions. The best TPMs are invisible when things go well and indispensable when they don't. 

Key Responsibilities 

• Own the master delivery plan: maintain the integrated roadmap across both Scrum teams, shared resources (Architect, ML, SDET), and external platform dependencies — with milestone-level clarity at all times.  
• Track and resolve cross-team dependencies: Agentic Engine, Core Platform (Temporal, MCP Gateway, Component Framework), ARC backend (Kafka event contracts, API dependencies), Design (component specs), and external vendors (email/SMS providers).  
• Run the delivery rhythm: sprint review calendar, cross-team sync cadence, dependency review meetings, and risk escalation forums — keeping the Director and VP Engineering informed without burying them in status updates.  
• Identify, quantify, and manage delivery risks: surface blockers early, drive resolution with urgency, and maintain a live risk register with mitigation owners and timelines.  
• Own cross-team technical communication: translate engineering status into language that Product, Business, and Executive stakeholders can act on — and translate business urgency back into engineering trade-off decisions.  
• Drive the release process: define release criteria, coordinate go/no-go decisions with Engineering, QA (Staff SDET), and Product, and manage production deployments across services.  
• Manage the dependency interface to the T1 Agentic Engine team: track which Intent, Skill, Policy, and MCP tool registrations are ready, which are blocked, and what the critical path impact is.  
• Continuously improve the delivery system: identify bottlenecks in the engineering process, drive retrospectives, and implement changes that sustainably increase throughput and quality.

Skills & Qualifications 

• 12+ years of technical program management experience, with at least 3 years at Staff level managing multi team programs at SaaS or platform companies.  
• Strong technical depth: able to read architecture diagrams, understand Kafka dependency graphs, evaluate API contract blockers, and participate credibly in engineering design discussions.  
• Proven experience managing complex, multi-team delivery programs with many external dependencies — including platform dependencies outside your direct control.  
• Expert facilitation of engineering delivery rituals: sprint planning, dependency reviews, release gates, post mortems, and architecture syncs.  
• Deep understanding of AI-native product delivery: what makes AI system delivery different from traditional software (eval requirements, model versioning, non-deterministic outputs, golden dataset dependencies).  
• Excellent written communication: can produce a crisp, executive-readable status update that tells the truth clearly and drives decisions.  
• Strong stakeholder management across Engineering, Product, Design, and Executive levels — comfortable managing up, across, and down.  

 
Good to Have  

• Experience managing delivery programs that involve both Java microservices and Python AI/ML engineering teams simultaneously.  
• Familiarity with agentic AI platform concepts: intent registries, MCP tools, skill/policy authoring, and eval frameworks — enough to track technical dependency status accurately.  
• Background in automotive retail technology or dealer management systems.  
• Prior experience working in a US-India distributed engineering organization.  
 

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

Job Overview:

We are seeking an experienced Senior Data Engineer to build and optimize scalable data platforms using Microsoft Fabric, Databricks (and/or Snowflake). The role focuses on designing reliable data pipelines, lakehouse and warehouse models, and semantic layers that enable enterprise analytics, BI, and AI/Gen AI use cases.

You will work closely with analytics, BI, and data science teams to deliver high-quality, performant, and governed data solutions, while driving best practices in data engineering, optimization, and platform design.

Key Responsibilities

• Design, build, and maintain end-to-end data solutions on Microsoft Fabric, Databricks, including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models.
• Implement scalable data ingestion, transformation, and loading (ETL/ELT) using Fabric Pipelines and PySpark.
• Develop robust data models and schemas optimized for analytics, reporting, and AI-driven consumption.
• Create and maintain semantic models to support Power BI and enterprise BI solutions.
• Engineer high-performance data solutions that meet requirements for throughput, scalability, quality, and security.
• Author efficient PySpark and SQL code for large-scale data transformation, data quality management, and business rule processing.
• Build reusable framework components for metadata-driven pipelines and automation.
• Optimize Lakehouse and Data Warehouse performance, including partitioning, indexing, Delta optimization, and compute tuning.
• Develop and maintain stored procedures and advanced SQL logic for operational workloads.
• Design and prepare feature-ready datasets for AI and GenAI applications.
• Collaborate with data scientists and ML engineers to productionize AI pipelines.
• Implement data governance and metadata practices required for responsible AI.
• Leverage Fabric, Databricks capabilities to orchestrate and monitor AI-related data workflows.
• Apply data governance, privacy, and security standards across all engineered assets.
• Implement monitoring, alerting, and observability best practices for pipelines and compute workloads.
• Drive data quality initiatives, including validation frameworks, profiling, and anomaly detection.
• Partner with analytics, BI, data science, and product teams to understand requirements and translate them into technical solutions.
• Mentor junior engineers and contribute to engineering standards and patterns.
• Participate in architecture reviews, technical design sessions, and roadmap planning.
• Develop and deliver dashboards and reports using Power BI and Tableau.

Required Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
• 7+ years of professional experience in data engineering or a related discipline.
• Mandatory hands-on expertise with Microsoft Fabric, Databricks or Snowflake including:
  • Pipelines
  • Notebooks
  • Lakehouse
  •  Data Warehouse
  • Semantic Models
• Advanced proficiency in PySpark for distributed data processing.
• Strong command of SQL for analytical and operational workloads.
• Experience developing and optimizing stored procedures and complex SQL transformations.
• Understanding of GenAI architectures, vectorization, embedding pipelines, and data preparation for LLM use cases.
• Strong knowledge of data modeling, ETL/ELT patterns, and modern data lakehouse principles.
• Experience designing and optimizing large-scale data pipelines in cloud environments (Azure preferred).
• Excellent problem-solving skills with the ability to analyze complex data workflows.
• Proficiency in creating interactive dashboards and reports using Power BI and Tableau.

The Mission

As a Lead Software Engineer working on the Appian platform, your mission is to be the technical anchor for our most ambitious engineering initiatives. You will ensure Appian is always fast, scalable, and resilient, regardless of the complexity our customers demand. While a Senior Engineer focuses on feature health, you are focused on platform evolution.

You will lead the design and orchestration of high-stakes systems, integrating cutting-edge AI into the core fabric of our product. This role demands a balance of elite coding mastery, visionary system architecture, and the ability to align technical roadmaps with Appian's overarching business strategy.

Key Responsibilities

The Lead Software Engineer isn't just "the best coder"—they are the architect of the team’s success and the guardian of our technical future.

• Technical Strategy & Roadmap: Work alongside Product Leadership to transform long-term business goals into scalable technical milestones. You don't just build features; you define the technical "North Star."
• Advanced Architecture: Lead the design of distributed, event-driven, and cloud-native systems. You are responsible for making high-level decisions on system boundaries, data consistency, and integration patterns.
• AI Orchestration & Innovation: Drive the adoption of AI-native engineering and an AI-native culture within the team. This includes using AI tools to improve developer productivity and implementing AI features into the platform to make the Appian platform more intelligent and autonomous.
• Architectural Governance: Set and enforce the "gold standard" for system design and code quality. You ensure that the codebase remains modular, maintainable, and free of crippling technical debt.
• Developer Multiplier: Create the "Golden Paths" and internal frameworks that empower other engineering teams to ship faster. You build the tools that make every other engineer more productive.
• High-Stakes Problem Solving: Act as the final escalation point for the "un-debuggable." You lead the resolution of critical production outages and architect long-term fixes for deep-seated performance bottlenecks.
• Mentorship & Influence: Cultivate a culture of excellence. You mentor Senior Engineers into future Leads and foster a high-growth environment through rigorous design reviews and technical coaching.

Required Qualifications

Education:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Educational background from a highly selective, premier engineering institution with a focus on Computer Science fundamentals is preferred

Experience:

• 10+ years of professional software engineering experience.
• Strong understanding of data structures, algorithms, design patterns, object-oriented as well as functional programming.
• Proven track record of leading technical initiatives from conception to global production deployment.
• Deep expertise in Java & modern web technologies, with a mastery of data structures, algorithms, and complex design patterns.
• Extensive experience building and scaling distributed systems in AWS cloud-native environments and modernization of applications/platforms.
• Strong knowledge of enterprise application architecture.
• Experience managing "large-scale" codebases where performance optimization and bottleneck identification are critical.
• Experience in AI/ML integration, specifically implementing intelligent features like RAG or agentic workflows into enterprise software is preferred.
  Experience with using AI tools and models like Amazon Q, Kiro, Claude is preferred.

Technical Skills:

• Full-Stack Authority: Expert-level proficiency in Java or similar major languages.
• Infrastructure & Orchestration: Hands-on experience with Docker, Kubernetes, and advanced CI/CD automation.
• Observability: Deep familiarity with performance monitoring and alerting stacks (e.g., Grafana, Prometheus, ELK).
• Cloud & Data: Strong experience with AWS services and modern database technologies (Relational, NoSQL, and Vector databases).
• Security & Compliance: Strong understanding of enterprise-grade security, including OAuth2, OIDC, and data encryption at rest/transit.

Soft Skills

• Strategic Communication: The ability to influence stakeholders and explain the "why" behind complex technical trade-offs in terms of business value.
• Systems Thinking: The ability to see how a change in one microservice ripples across the entire ecosystem.
• Radical Accountability: A bias for action and a sense of ownership over the entire platform’s stability and success.
• Mentorship: A genuine passion for leveling up the collective intelligence of the engineering organization.

The Mission

As a Lead Software Engineer working on the Appian platform, your mission is to be the technical anchor for our most ambitious engineering initiatives. You will ensure Appian is always fast, scalable, and resilient, regardless of the complexity our customers demand. While a Senior Engineer focuses on feature health, you are focused on platform evolution.

You will lead the design and orchestration of high-stakes systems, integrating cutting-edge AI into the core fabric of our product. This role demands a balance of elite coding mastery, visionary system architecture, and the ability to align technical roadmaps with Appian's overarching business strategy.

Key Responsibilities

The Lead Software Engineer isn't just "the best coder"—they are the architect of the team’s success and the guardian of our technical future.

• Technical Strategy & Roadmap: Work alongside Product Leadership to transform long-term business goals into scalable technical milestones. You don't just build features; you define the technical "North Star."
• Advanced Architecture: Lead the design of distributed, event-driven, and cloud-native systems. You are responsible for making high-level decisions on system boundaries, data consistency, and integration patterns.
• AI Orchestration & Innovation: Drive the adoption of AI-native engineering and an AI-native culture within the team. This includes using AI tools to improve developer productivity and implementing AI features into the platform to make the Appian platform more intelligent and autonomous.
• Architectural Governance: Set and enforce the "gold standard" for system design and code quality. You ensure that the codebase remains modular, maintainable, and free of crippling technical debt.
• Developer Multiplier: Create the "Golden Paths" and internal frameworks that empower other engineering teams to ship faster. You build the tools that make every other engineer more productive.
• High-Stakes Problem Solving: Act as the final escalation point for the "un-debuggable." You lead the resolution of critical production outages and architect long-term fixes for deep-seated performance bottlenecks.
• Mentorship & Influence: Cultivate a culture of excellence. You mentor Senior Engineers into future Leads and foster a high-growth environment through rigorous design reviews and technical coaching.

Required Qualifications

Education:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Educational background from a highly selective, premier engineering institution with a focus on Computer Science fundamentals is preferred

Experience:

• 10+ years of professional software engineering experience.
• Strong understanding of data structures, algorithms, design patterns, object-oriented as well as functional programming.
• Proven track record of leading technical initiatives from conception to global production deployment.
• Deep expertise in Java & modern web technologies, with a mastery of data structures, algorithms, and complex design patterns.
• Extensive experience building and scaling distributed systems in AWS cloud-native environments and modernization of applications/platforms.
• Strong knowledge of enterprise application architecture.
• Experience managing "large-scale" codebases where performance optimization and bottleneck identification are critical.
• Experience in AI/ML integration, specifically implementing intelligent features like RAG or agentic workflows into enterprise software is preferred.
  Experience with using AI tools and models like Amazon Q, Kiro, Claude is preferred.

Technical Skills:

• Full-Stack Authority: Expert-level proficiency in Java or similar major languages.
• Infrastructure & Orchestration: Hands-on experience with Docker, Kubernetes, and advanced CI/CD automation.
• Observability: Deep familiarity with performance monitoring and alerting stacks (e.g., Grafana, Prometheus, ELK).
• Cloud & Data: Strong experience with AWS services and modern database technologies (Relational, NoSQL, and Vector databases).
• Security & Compliance: Strong understanding of enterprise-grade security, including OAuth2, OIDC, and data encryption at rest/transit.

Soft Skills

• Strategic Communication: The ability to influence stakeholders and explain the "why" behind complex technical trade-offs in terms of business value.
• Systems Thinking: The ability to see how a change in one microservice ripples across the entire ecosystem.
• Radical Accountability: A bias for action and a sense of ownership over the entire platform’s stability and success.
• Mentorship: A genuine passion for leveling up the collective intelligence of the engineering organization.

#LI-EC1 

Job Description

We are looking for a Senior QA Engineer / SDET to drive quality across our AI-native backend services and platform systems. You will own test automation strategy, release quality gates, and quality engineering practices — working closely with backend engineers (Java + Python), product managers, and platform architects. This role focuses heavily on validating hexagonal architecture adapters, Kafka event pipelines, multi-database correctness, and AI scoring model outputs.

Key Responsibilities

• Design, build, and scale automated test frameworks for Java microservices built on hexagonal architecture — with distinct test strategies for the domain core, adapter layers (MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, Redis/Aerospike), and external integrations.

• Develop and maintain comprehensive test suites: functional, integration (Testcontainers), regression, contract, and end-to-end across all adapter implementations.

• Validate Kafka event pipelines: consumer behavior, event ordering, idempotency, poison pill handling, and dead-letter queue processing. 

• Validate MongoDB document integrity, PostgreSQL relational consistency, Cosmos DB partition correctness, and Elasticsearch index accuracy across service boundaries.

• Design and execute golden dataset test scenarios — seeding realistic dealer and customer data to validate scoring accuracy, suppression correctness, and attribution logic.

• Validate Python-based AI/ML service outputs: scoring model results, recommendation correctness, and LLM response safety gates. 

• Collaborate closely with backend engineers and architects to embed quality early in hexagonal domain design and adapter implementation.

• Drive testability improvements by influencing API design, logging, observability, and error handling.

• Own release quality and go/no-go decisions by defining and tracking quality gates in CI/CD pipelines.

• Define and monitor quality metrics: test coverage, defect leakage, flakiness, MTTR, and automation ROI. 

• Lead root cause analysis for production issues and drive preventive measures.

• Mentor junior QA/SDET engineers and set best practices across teams.

Skills & Experience

• 6+ years of hands-on experience in QA Engineering, Test Automation, or SDET roles.

• Strong test automation expertise using modern Java-based frameworks; working knowledge of Python test frameworks (pytest) is a strong plus.

• Deep experience testing distributed microservices, REST APIs, and Kafka-based architectures.

• Experience with Testcontainers for integration testing across MongoDB, PostgreSQL, Kafka, and Elasticsearch locally.

• Strong understanding of Kafka testing: consumer behavior, event ordering guarantees, and idempotency validation.

• Experience with MongoDB and PostgreSQL testing patterns: data integrity, schema migration validation, multi-tenant isolation verification.

• Familiarity with Elasticsearch test strategies: index correctness, relevance, and query result validation.

• Experience with CI/CD pipeline integration (GitHub Actions, Jenkins, or equivalent).

• Familiarity with containerized environments (Docker, Kubernetes).

• Excellent problem-solving, communication, and collaboration skills.

Preferred Skills

• Experience validating AI/ML model outputs and scoring pipeline correctness.

• Exposure to contract testing (Pact or similar) and service virtualization for hexagonal adapter boundaries.

• Experience with performance, load, and chaos testing (JMeter, Gatling, k6) against Elasticsearch and Kafka.

• Background in DevOps or Site Reliability Engineering practices.

Perks & Benefits

• Competitive compensation and generous stock options. 

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies. 

Job Description

We are seeking a Staff SDET to own the quality architecture for our AI-native platform. This is not a test execution role — it is a quality engineering leadership role. You will design and own the test strategy across all layers of the hexagonal architecture (domain core, adapters, integration, end-to-end), establish quality gates for AI model outputs, build the golden dataset evaluation framework, and set the engineering bar for Senior SDETs and QA engineers on both Scrum teams. Nothing ships without your sign-off.

Key Responsibilities

• Own the complete quality architecture: define test strategies at each hexagonal layer — domain core unit tests, adapter integration tests (Testcontainers), service-to-service contract tests (Pact), and end-to-end scenario tests.

• Design and build the golden dataset evaluation framework: seed realistic multi-tenant dealer/customer data across MongoDB, PostgreSQL, Cosmos DB, Elasticsearch, and Kafka, and define assertion criteria for scoring accuracy, suppression correctness, and attribution logic. 

• Establish AI quality gates: define evaluation criteria for ML model outputs (scoring, recommendations), LLM response quality, RAG retrieval accuracy (precision@k, recall), and agentic workflow correctness.

• Architect test infrastructure: Testcontainers configurations for MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, and Redis/Aerospike — enabling fully local integration test runs.

• Own CI/CD quality pipeline: define what automated tests run at commit, PR, staging, and pre-release gates — with blocking quality thresholds.

• Define and track quality metrics: test coverage per hexagonal layer, defect leakage, flakiness rate, MTTR, and automation ROI.

• Lead root cause analysis for production escapes — own post-mortems and preventive measure implementation. 

• Mentor Senior SDETs and QA engineers across both teams; conduct design reviews for test frameworks and golden dataset designs.

• Influence backend and frontend engineers on testability: drive API design, logging, observability, and error handling that makes services intrinsically testable. 

Skills & Experience

• 8+ years of QA Engineering, Test Automation, or SDET experience with strong hands-on engineering depth.

• Deep expertise designing test strategies for hexagonal architecture: proven ability to test domain cores independently from adapters, and adapters independently from each other.

• Strong programming skills in Java (primary) and Python — able to write production-quality test frameworks, not just test scripts. 

• Expert-level Testcontainers experience across MongoDB, PostgreSQL, Kafka, Elasticsearch, and Redis/Aerospike. 

• Experience with contract testing (Pact or similar) for service boundary validation and service virtualization.

• Deep Kafka testing expertise: consumer group behavior, event ordering guarantees, idempotency, and dead-letter queue validation.

• Experience designing golden dataset strategies: multi-tenant data seeding, realistic event sequences, and deterministic assertion design.

• Experience integrating quality gates into CI/CD pipelines with meaningful blocking thresholds.

• Strong understanding of AI/ML output validation: scoring correctness, RAG retrieval quality metrics, and agentic workflow eval design.

Preferred Skills

• Experience with performance, load, and chaos testing (Gatling, k6) against Kafka, Elasticsearch, and MongoDB at scale.

• Background in AI/ML quality engineering: eval frameworks (RAGAS or similar), model regression detection, and LLM safety testing.

• Prior experience owning quality for a platform serving multiple engineering teams (quality platform ownership).

• Familiarity with Cosmos DB testing patterns and eventual consistency validation strategies.

Perks & Benefits

• Competitive compensation and generous stock options.

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

As a Lead Automation QA Engineer, you will champion world-class software quality by architecting and executing advanced, hands-on automation across complex business workflows. Though you may provide strategy and mentorship, your core focus will be as a technical individual contributor running sophisticated, E2E test automation—including data, API, mobile, and cross-platform business process validations spanning the full Lead-to-Cash cycle (Salesforce, Implementation, and NetSuite). You’ll also adopt AI-based test automation, including LLM and RAG system validations.

Responsibilities

Hands-On Test Automation:

• E2E Business Process Validation:
• Design and execute automated E2E tests spanning the full Lead-to-Cash cycle, including Salesforce, downstream processes, and financial handoff to NetSuite.
• Orchestrate multi-system test scenarios to validate data flows, business process logic, integrations, and error handling across Salesforce and NetSuite.
• Develop automated test scripts to ensure synchronization and data integrity between CRM, integrated system, and ERP for business-critical workflows.
• Data Validation:
• Write and automate SQL queries for multi-source data verification, ensuring consistent, accurate information across connected systems.
• Perform automated backend checks as opportunities progress through different pipeline stages from Lead to Revenue realization.
• API & Integration Testing:
• Build and maintain robust API validation suites using Rest Assured or similar frameworks, covering all RESTful interfaces connecting Salesforce, Integrated system, and NetSuite.
• Validate integration points and data exchange between systems.
• Mobile Test Automation:
• Create and execute automated mobile tests (Appium, Espresso, XCUITest) for mobile components of business processes (if applicable).
• AI-Driven QA:
• Leverage AI-powered test automation tools and approaches to optimize and expand test coverage.
• Design and manage automated validation of Large Language Model (LLM) or Retrieval-Augmented Generation (RAG)-enabled workflows.
• DevOps Integration:
• Integrate automated E2E and component tests into CI/CD pipelines for continuous validation.

QA Leadership:

• Mentor team members in test strategy for multi-system, E2E automation.
• Review test plans and ensure adoption of QA best practices for cross-platform business process validation.
• Collaborate with cross-functional teams (Salesforce admins, implementation engineers, ERP developers) to ensure quality across business processes.

Requirements

• 8+ years’ automation QA experience, with proven E2E validation across business process systems.
• Hands-on experience automating tests across Salesforce, middleware/implementation platforms, and ERP systems like NetSuite.
• Advanced SQL query skills for backend data validation and reconciliation.
• Strong experience with API automation (Rest Assured or similar) and automated UI testing tools.
• Experience with mobile automation frameworks (Appium, Espresso, XCUITest, etc.).
• Familiarity or experience with AI/LLM/RAG or willingness to learn and implement.
• Proficient with CI/CD, Agile workflows, and test automation best practices.
• Excellent analytical, troubleshooting, and communication skills.

Why we're hiring:

Detection Engineering is responsible for designing, developing, and maintaining high-fidelity detection logic across enterprise security platforms. This role focuses on proactive threat detection, automation-first practices, and continuous improvement of detection coverage and accuracy, supporting the WPP SOC transformation into an Autonomic Security Operations model.

What you'll be doing:

• Develop, test, and maintain detection rules and logic across SIEM, EDR, NDR, and cloud-native platforms.
•  Regularly review and enhance detection logic to improve accuracy, reduce noise, and align with evolving threats.
• Work with wider WPP engineering teams to ensure high-quality, normalized telemetry for effective detection.
• Automate detection rule deployment, QA, and version control using scripting and CI/CD pipelines.

Root Cause Analysis (RCA)

• Conduct RCA on missed detections, delayed responses, and high-severity incidents.
•  Identify technical and process-level causes of detection failures or inefficiencies.
• Drive corrective actions based on RCA outcomes (e.g., rule improvements, visibility gaps).
• Continuous Security Improvement (CSI)
• Maintain a CSI backlog (detection gaps, telemetry blind spots, false positives to reduce).
•  Analyze detection performance metrics to identify trends and opportunities for improvement.
• Align detection priorities with business risk and the SOC transformation roadmap.
• Cross-Team Collaboration
• Collaborate with SOC, Incident Response, and Threat Hunting teams to operationalize detection improvements.
•  Work with Threat Intelligence teams to integrate emerging TTPs into detection logic.
• Contribute to purple team exercises by validating detection logic against simulated attack paths.

Strategic Alignment to GCAT SOC10x

• 10X People: Continuous learning and knowledge sharing within the team.
• 10X Process: Embed agile workflows and automation-first principles.
• 10X Technology: Leverage AI/ML for detection tuning and anomaly detectio.
• 10X Visibility: Ensure comprehensive telemetry ingestion and observability.
• 10X Speed: Reduce detection-to-response cycle through orchestration and automation.

What you'll need:

Technical Expertise

• Strong knowledge of SIEM, SOAR, EDR, and cloud security platforms.
• Proficiency in scripting and automation (Python, PowerShell).
• Familiarity with detection-as-code principles and CI/CD pipelines.
• Understanding of MITRE ATT&CK framework and threat-informed defense.

Collaboration & Communication

•  Ability to work closely with SOC analysts, threat hunters, and engineers.
• Skilled in documenting detection logic and RCA outcomes.

Certifications (Preferred)

• GIAC GCTI, GCFA, or equivalent advanced security certifications.

Key Attributes

• Automation-first mindset with focus on scalability and resilience.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork capabilities.

Who you are:

You're open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.

You're optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.

You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.

What we'll give you:

Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.

Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.

Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?

Job Description

We are looking for a Senior QA Engineer / SDET to drive quality across our AI-native backend services and platform systems. You will own test automation strategy, release quality gates, and quality engineering practices — working closely with backend engineers (Java + Python), product managers, and platform architects. This role focuses heavily on validating hexagonal architecture adapters, Kafka event pipelines, multi-database correctness, and AI scoring model outputs.

Key Responsibilities

• Design, build, and scale automated test frameworks for Java microservices built on hexagonal architecture — with distinct test strategies for the domain core, adapter layers (MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, Redis/Aerospike), and external integrations.

• Develop and maintain comprehensive test suites: functional, integration (Testcontainers), regression, contract, and end-to-end across all adapter implementations.

• Validate Kafka event pipelines: consumer behavior, event ordering, idempotency, poison pill handling, and dead-letter queue processing. 

• Validate MongoDB document integrity, PostgreSQL relational consistency, Cosmos DB partition correctness, and Elasticsearch index accuracy across service boundaries.

• Design and execute golden dataset test scenarios — seeding realistic dealer and customer data to validate scoring accuracy, suppression correctness, and attribution logic.

• Validate Python-based AI/ML service outputs: scoring model results, recommendation correctness, and LLM response safety gates. 

• Collaborate closely with backend engineers and architects to embed quality early in hexagonal domain design and adapter implementation.

• Drive testability improvements by influencing API design, logging, observability, and error handling.

• Own release quality and go/no-go decisions by defining and tracking quality gates in CI/CD pipelines.

• Define and monitor quality metrics: test coverage, defect leakage, flakiness, MTTR, and automation ROI. 

• Lead root cause analysis for production issues and drive preventive measures.

• Mentor junior QA/SDET engineers and set best practices across teams.

Skills & Experience

• 6+ years of hands-on experience in QA Engineering, Test Automation, or SDET roles.

• Strong test automation expertise using modern Java-based frameworks; working knowledge of Python test frameworks (pytest) is a strong plus.

• Deep experience testing distributed microservices, REST APIs, and Kafka-based architectures.

• Experience with Testcontainers for integration testing across MongoDB, PostgreSQL, Kafka, and Elasticsearch locally.

• Strong understanding of Kafka testing: consumer behavior, event ordering guarantees, and idempotency validation.

• Experience with MongoDB and PostgreSQL testing patterns: data integrity, schema migration validation, multi-tenant isolation verification.

• Familiarity with Elasticsearch test strategies: index correctness, relevance, and query result validation.

• Experience with CI/CD pipeline integration (GitHub Actions, Jenkins, or equivalent).

• Familiarity with containerized environments (Docker, Kubernetes).

• Excellent problem-solving, communication, and collaboration skills.

Preferred Skills

• Experience validating AI/ML model outputs and scoring pipeline correctness.

• Exposure to contract testing (Pact or similar) and service virtualization for hexagonal adapter boundaries.

• Experience with performance, load, and chaos testing (JMeter, Gatling, k6) against Elasticsearch and Kafka.

• Background in DevOps or Site Reliability Engineering practices.

Perks & Benefits

• Competitive compensation and generous stock options. 

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies. 

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell® Fusion, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior. Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day.

We are embarking on a transformative journey with DriveWell Atlas, a groundbreaking initiative to build a family of novel AIs on telematics data. As a Senior Machine Learning Engineer, Foundation Models on the DriveWell Atlas team, you will help design and develop next-generation AI models that advance CMT’s capabilities in risk assessment, driver engagement, crash detection, and claims processing. This role offers the opportunity to work at the intersection of cutting-edge AI research and real-world telematics applications.

CMT is looking for a collaborative, customer-committed, and creative Senior Machine Learning Engineer, Foundation Models who wants to join us in making roads safer by making drivers better!

Responsibilities:

• Contribute to the design, training, and deployment of novel AI models for telematics applications
• Develop algorithms that model physical phenomena associated with vehicle and human movement
• Explore and implement advanced self-supervised learning methods tailored to multi-modal telematics sensor data
• Fine-tune upstream pretrained models or leverage their embeddings to solve downstream telematics tasks such as crash detection, driver risk scoring, and claims processing
• Build models robust to noise, missing data, and diverse real-world operating conditions
• Collaborate with engineers and product teams to integrate AI models into production systems
• Develop scalable training and inference pipelines using frameworks such as Ray, PyTorch DDP, or Horovod
• Optimize models for efficient deployment across cloud and edge/mobile environments
• Stay current with AI/ML research, applying new techniques to real-world telematics challenges
• Document and present findings, contributing to CMT’s AI/ML knowledge base
• Support junior team members through code reviews, collaboration, and knowledge sharing
• Complete any additional tasks as they arise

Qualifications:

• Bachelor’s degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field
• 4+ years of relevant experience in AI/ML (post-degree)
• Strong hands-on experience developing and training deep learning models, preferably transformers for time-series or multimodal data
• Familiarity with self-supervised learning and representation learning on noisy sensor data
• Proficiency in Python and data science libraries (e.g., Pandas, NumPy, scikit-learn)
• Strong experience with PyTorch (preferred) or TensorFlow for deep learning
• Practical experience with distributed training methods and efficient model training
• Experience with data processing pipelines and ML infrastructure (e.g., Spark, Airflow, Docker, AWS/GCP/Azure)
• Excellent problem-solving skills and ability to translate complex business problems into AI solutions
• Strong communication skills to effectively present technical concepts to diverse audiences
• Product-focused mindset with a track record of delivering impactful ML solutions

Nice to Haves:

• Master’s or PhD preferred
• Experience with model interpretability and explainability techniques (XAI)
• Familiarity with ethical AI principles, bias detection, and mitigation strategies
• Exposure to MLOps practices for managing the ML lifecycle
• Publications or open-source contributions in AI/ML

Compensation and Benefits:

• Fair and competitive salary based on skills and experience
• Equity may be awarded in the form of Restricted Stock Units (RSUs)
• Medical Benefits (Health insurance, Personal accident insurance, Group term life insurance), gratuity, parental leave, sick leave and public holidays
• Employees are eligible for flexible allowances which includes Leave Travel Assistance, Telephone/Mobile Expenses, Professional development expenses, Meals Coupon, Vehicle Reimbursement
• Flexible scheduling and work from home policy depending on role and responsibilities

Additional Perks:

• Feel great working to improve road safety around the world!
• Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness
• Extensive education and employee assistance programs
• CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all!

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

Job Description

Key Responsibilities

• Own end-to-end delivery of CI/CD pipelines, infrastructure as code, and deployment automation workflows. 
• Collaborate with application, infrastructure, and security teams to drive automation, system reliability, and operational excellence. 
• Establish and track key metrics (KPIs) for deployment frequency, change lead time, incident reduction, and operational resilience. 
• Ensure compliance and security requirements are met through robust tooling and effective processes (e.g., secrets management, vulnerability scanning, audit logging). 
• Manage resource planning, hiring, and performance reviews; foster a collaborative and inclusive team environment. 
• Report progress, risks, and key outcomes to senior leadership; contribute to technology, roadmaps and budget planning. 

Skills and Experience

• Bachelor’s/master’s in computer science, Engineering, or related field, or equivalent practical experience. 
• 5+ years of experience in DevOps or SRE roles, including large-scale automation and modern infrastructure management. 
• Deep experience with modern DevOps tooling and practices (e.g., Kubernetes, Terraform, Jenkins, GitHub Actions, AWS/GCP/Azure). 
• Proven expertise in automation, configuration management, monitoring/alerting, and incident response. 
• Solid understanding of security best practices for cloud-native environments (e.g., IAM, RBAC, encryption, compliance frameworks). 
• Strong communication skills, with the ability to effectively manage stakeholders, prioritize work, and build high-performing teams. 

Job Description

Key Responsibilities

• Own end-to-end delivery of CI/CD pipelines, infrastructure as code, and deployment automation workflows. 
• Collaborate with application, infrastructure, and security teams to drive automation, system reliability, and operational excellence. 
• Establish and track key metrics (KPIs) for deployment frequency, change lead time, incident reduction, and operational resilience. 
• Ensure compliance and security requirements are met through robust tooling and effective processes (e.g., secrets management, vulnerability scanning, audit logging). 
• Manage resource planning, hiring, and performance reviews; foster a collaborative and inclusive team environment. 
• Report progress, risks, and key outcomes to senior leadership; contribute to technology, roadmaps and budget planning. 

Skills and Experience

• Bachelor’s/master’s in computer science, Engineering, or related field, or equivalent practical experience. 
• 5+ years of experience in DevOps or SRE roles, including large-scale automation and modern infrastructure management. 
• Deep experience with modern DevOps tooling and practices (e.g., Kubernetes, Terraform, Jenkins, GitHub Actions, AWS/GCP/Azure). 
• Proven expertise in automation, configuration management, monitoring/alerting, and incident response. 
• Solid understanding of security best practices for cloud-native environments (e.g., IAM, RBAC, encryption, compliance frameworks). 
• Strong communication skills, with the ability to effectively manage stakeholders, prioritize work, and build high-performing teams. 

Who we seek:

We’re looking for a Senior Data Platform Engineer to join our Data Platform team. The ideal candidate will have extensive experience with data engineering, specifically with Kafka and Elasticsearch, to design and maintain our data platforms. You will work closely with cross-functional teams to ensure the scalability and reliability of our data solutions.

Job Summary:
As a Senior Data Platform Engineer, you'll be responsible for design, development, maintenance, troubleshooting, and implementation of our big data architecture. Your expertise in Elastic, Kafka, and node.js will be critical in ensuring the scalability and performance of our data systems.

What you’ll do:

• Implement data processing pipelines using Kafka for real-time data streaming.
• Optimize and manage search capabilities using Elastic technologies.
• Collaborate with product managers, data analysts, and other stakeholders to gather requirements and translate them into technical specifications.
• Oversee code reviews, ensure best practices in coding and data handling, and maintain high-quality standards in software development.
• Stay up-to-date with emerging trends and technologies in big data and recommend improvements to our architecture and processes.
• Troubleshoot and resolve issues in a timely manner to minimize downtime and ensure system reliability.

What you’ll bring:

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
• 8+ years of experience in the software engineering field. 
• 5+ years of experience in big data technologies, with a focus on MongoDB, Elastic Stack and Kafka.
• Proficiency in Node.js  with NestJS framework and TypeScript.
• Strong understanding of data modelling, ETL processes, and data warehousing.
• Excellent problem-solving abilities and strong analytical skills.
• A solid understanding of CI/CD principles.
• Experience working with both external and in-house APIs and SDKs 

Advantages:

• Experience with Java
• Experience with Docker, Kubernetes
• Experience with cloud platforms (e.g., AWS or Azure) 

What’s in it for you?!

Our people are the foundation of our success, and we prioritize offering a wide range of benefits that make our team happier and healthier.

•    Equity participation - everyone shares in our success
•    Hybrid work 
•    Team fun & company outings
•    Statutory benefits and leave benefits
•    Health Insurance coverage 

Our Values:

We look for people who embody our values - Care, Do, Try & Shine.

• Care - We care about our customers and each other
• Do - We do what it takes to make a positive impact
• Try- We try our best and we don’t give up
• Shine- We shine and make it our mission to always stand out

#LI-HYBRID

#LI-EV2

Who we seek:

BigID is looking for a Principal Premium Support Engineer to join our team. This is a hands-on, client-facing support role where you will be responsible for:

• Providing exceptional product assistance
• Helping with configuration questions
• Capturing enhancement requests
• Troubleshooting and researching product issues
• Collaborating effectively with diverse internal teams and external customers, even in challenging situations.
• Partnering with Cross-functional teams
• Facilitating escalation
• Expediting resolutions
• Correcting and maintaining account health
• Managing customer accounts from a technical support perspective

You will work with customers, other support and services team members, and our engineering organization to resolve complex problems, acting as an advocate for our clients within BigID. You will balance both proactive monitoring, discussion and planning to develop actionable growth paths for your assigned customers as well as reactive trouble shooting and quick issue resolution to arrive at optimal account health and product adoption. Successful candidates will have prior experience providing technical support to enterprise customers at the Tier 2 or Tier 3 level. A software development background and/or escalation management experience is a strong plus.

What you’ll do:

• Collaborate closely with assigned clients to understand their requests, develop appropriate action plans to address their concerns or questions, and engage necessary resources to execute these plans.
• Provide assigned clients with timely updates on their concerns or questions throughout the resolution process.
• Work closely with our Engineering and Product Management teams to document product issues, field-raised enhancement requests, and potential product improvements.
• Act as a "Voice-of-the-Customer" to help prioritize issues, requests, and improvements.
• Partner with our Client Services team during solution deployment engagements and assist in resolving encountered issues.
• Cultivate productive dynamics with the other account team members to ensure proper alignment and shared customer temperature assessments.
• Develop in-depth technical knowledge of the product and its interactions within highly varied technology environments.

What you’ll bring:

• 6+ years of experience in information technology or technical product support, with at least 4 years in a customer-facing role, preferably within enterprise corporate environments.
• An undergraduate degree in Computer Science, Information Technology/Systems, or other related technical disciplines. (Extensive professional experience may be considered in lieu of a formal degree.)
• Meaningful experience with the installation, configuration, and management of UNIX or Linux-based Operating Systems, including:
  • Basic shell proficiency (bash, sh, ksh, tcsh, etc.)
  • Experience with package management systems (apt/dpkg, yum/rpm, etc.)
  • File archiving tools (tar, gz, zip, bz2)
  • Remote access and file transfer protocols (SSH, SCP, SFTP)
  • File sharing technology (NFS, SMB/CIFS)
  • Authentication frameworks (LDAP, Kerberos)
• Basic experience with some RDBMS, such as Microsoft SQL Server, Oracle Database, PostgreSQL, MySQL/MariaDB, IBM DB2, etc.
• Excellent communication and organization skills, with a proven ability to maintain composure and effectiveness under pressure.
• Strong troubleshooting skills and a methodical approach to issue resolution.
• Demonstrated adaptability and resilience in navigating complex or ambiguous situations.
• Dedication to expertly resolving challenging issues and building strong customer loyalty.
• English fluency (written and spoken).

What’s in it for you?!

Our people are the foundation of our success, and we prioritize offering a wide range of benefits that make our team happier and healthier.

•    Equity participation - everyone shares in our success
•    Hybrid work 
•    Opportunities for professional growth
•    Team fun & company outings
•    Statutory benefits and leave benefits
•    Health Insurance coverage 

Our Values:

We look for people who embody our values - Care, Do, Try & Shine.

• Care - We care about our customers and each other
• Do - We do what it takes to make a positive impact
• Try- We try our best and we don’t give up
• Shine- We shine and make it our mission to always stand out

#LI-Hybrid

#LI-EV2