HR POD - Hiring Talent Globally

• Write engaging, SEO-friendly website content and blog articles. • Research technical topics and convert them into clear, reader-friendly content. • Create original, well-structured, and factually accurate content. • Use AI tools effectively to support research, ideation, and editing while ensuring the final content remains natural and minimally AI-generated. • Proofread and edit content for clarity, grammar, tone, and consistency. • Meet deadlines and deliver high-quality content on an ongoing basis.

• Lead technical discovery sessions with enterprise customers to understand business objectives, deployment requirements, and success criteria. • Scope and execute proof-of-concepts, pilot programs, and production deployment initiatives. • Conduct load testing and evaluations to validate model architectures and deployment configurations. • Design and implement end-to-end AI solutions within complex enterprise environments. • Build production-grade AI and machine learning systems that meet enterprise performance, security, and compliance requirements. • Conduct model evaluations, benchmarking, and performance testing. • Advise customers on model selection strategies and deployment architectures. • Support fine-tuning methodologies, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Fine-Tuning (RFT). • Develop evaluation frameworks to measure model quality and business impact. • Design scalable inference architectures that support enterprise workloads. • Work with GPU infrastructure, containerized applications, Kubernetes, and cloud platforms. • Collaborate with customer engineering teams to optimize system reliability, latency, scalability, and performance. • Address infrastructure, security, and compliance challenges to ensure successful production deployments. • Present technical recommendations to engineering teams and executive leadership. • Build trusted relationships with customer stakeholders, identify champions, address objections, and drive successful deployments. • Identify recurring customer pain points and provide actionable feedback to internal product and engineering teams. • Influence product roadmap decisions through customer insights and field experience.

• Configure, customize, and enhance ServiceNow modules, including ITSM, ITOM, HRSD, and CSM, through UI Policies, Business Rules, Client Scripts, and Script Includes. • Design, develop, and implement complex workflows and process automations using Flow Designer and Workflow Editor. • Support and optimize ITSM, ITOM, Analytics, CMDB, and Discovery capabilities across the platform. • Provide architectural guidance and contribute to the long-term evolution and scalability of the ServiceNow platform. • Design, develop, and maintain Scripted REST APIs within scoped applications. • Develop, troubleshoot, and maintain ServiceNow scripting solutions using Glide APIs, including GlideRecord, GlideSystem, and GlideAjax. • Build and maintain integrations with third-party systems using REST/SOAP APIs, Integration Hub, and JDBC. • Design and develop custom Service Portal pages and widgets using HTML, CSS, AngularJS, and Bootstrap. • Collaborate with stakeholders and business analysts to gather requirements and translate them into scalable technical solutions. • Perform unit testing, support UAT activities, and participate in code reviews to ensure quality, performance, and maintainability. • Manage update sets, platform upgrades, and patch deployments while minimizing business disruption. • Maintain comprehensive technical documentation, including configurations, process flows, integrations, and operational procedures.

• Own core product positioning and ensure consistent alignment across all messaging and GTM activities. • Develop and tailor messaging by market to ensure relevance across different geographies and customer segments. • Build the complete sales enablement asset library from scratch, including battle cards, one-pagers, case studies, and pitch decks. • Equip AEs and SDRs with market-specific, high-impact collateral to support deal execution. • Create ROI frameworks and objection-handling materials to strengthen sales conversations. • Manage and guide the content team to ensure high-quality output and strategic alignment. • Own the editorial calendar and overarching narrative framework across all content initiatives. • Ensure all content is tightly aligned with ICP definitions and product positioning. • Define content KPIs and establish a consistent review and performance tracking cadence. • Own the competitive intelligence function and maintain a structured view of the competitive landscape. • Maintain a live competitor tracker across conversational commerce, WhatsApp tools, and AI-powered shopping ecosystems. • Translate competitive insights into positioning updates, battle cards, and internal sales enablement materials. • Deliver quarterly competitive landscape briefs to leadership. • Participate in product roadmap reviews and collaborate closely with the product team. • Own GTM planning for feature and product launches across all key releases. • Translate product roadmap decisions into clear, compelling market-facing narratives. • Own centralized ICP definition and ongoing validation while coordinating cross-functional execution of all launch assets. • Conduct win/loss analysis and structured customer interviews to generate actionable insights. • Continuously feed customer and market insights into sales, product, and marketing functions. • Support research and insights for expansion into new geographic markets.

• Serve as the primary point of contact for clients, building strong relationships and understanding their business goals to align marketing strategies accordingly. • Develop and manage marketing campaigns across email, SMS, and push notification channels, leveraging AI tools for analytics, optimization, and creative execution. • Analyze campaign performance, identify trends, and provide actionable insights and recommendations to improve future campaigns. • Collaborate with creative, analytics, and strategy teams to ensure campaigns are aligned, executed efficiently, and meet client objectives. • Manage end-to-end campaign execution, ensuring projects are delivered on time, within budget, and according to client expectations. • Continuously monitor campaign performance and optimize strategies, targeting, and creative elements to improve engagement, conversions, and ROI. • Lead regular client meetings and presentations to review campaign performance, discuss upcoming initiatives, and maintain alignment on goals and strategy.

• Design, build, and maintain production-grade ML pipelines on Databricks. • Operationalize ML models, including deployment, monitoring, and full lifecycle management. • Build and maintain CI/CD pipelines for ML workflows. • Develop and manage real-time and streaming data pipelines. • Collaborate closely with Data Scientists to efficiently productionize models. • Implement model versioning, experiment tracking, and ensure reproducibility. • Define and enforce ML best practices, governance, and quality standards. • Monitor model performance and data drift, and implement automated retraining strategies. • Optimize performance, scalability, and cost of distributed workloads. • Contribute to platform design for low-latency inference and scalable model serving.

• Design, develop, and maintain complex ETL pipelines in Databricks, ensuring scalable and high-performance data integration across multiple source systems. • Implement and optimize medallion architecture within Databricks by establishing structured data zones (raw, curated, and trusted) to support governed, enterprise-level reporting. • Develop and enhance dimensional data models that provide analytics-ready business views and support automated dashboards and KPI reporting frameworks. • Collaborate closely with cross-functional teams, including data stewards, IT teams, and business stakeholders, to translate operational requirements into effective technical solutions while proactively identifying dependencies and driving alignment. • Contribute to architectural and technical decisions by recommending best practices, challenging assumptions where necessary, and ensuring the scalability, durability, and flexibility of the data platform. • Proactively identify and resolve integration issues, data quality concerns, and process bottlenecks, while providing actionable insights and constructively highlighting potential project risks or inefficiencies. • Support documentation and knowledge-sharing initiatives to enable teams and clients to independently maintain and enhance data solutions over time.

• Design, develop, and enhance existing frameworks for test infrastructure. • Create and maintain automation test scripts using an object-oriented approach. • Execute automated test scripts across installation, functional, performance, and load testing scenarios. • Develop and maintain comprehensive test reports. • Train and mentor team members on automation testing concepts, providing guidance as needed. • Coordinate and prioritize test development activities while working across multiple development teams and software projects. • Contribute to the consistent and predictable delivery of high-quality releases. • Research, recommend, and implement tools to continuously improve and expand automation capabilities.

• Design, build, and maintain scalable cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Pulumi. • Develop, implement, and optimize CI/CD pipelines to enable efficient and reliable software delivery. • Ensure cloud infrastructure adheres to best practices for security, scalability, availability, and performance. • Automate infrastructure provisioning and deployment processes following DevOps best practices. • Develop and maintain monitoring, logging, and alerting systems using tools such as CloudWatch, Prometheus, Grafana, or ELK. • Collaborate closely with development and QA teams to ensure smooth and efficient cloud operations. • Actively contribute as part of a cross-functional Agile/Scrum team. • Troubleshoot and resolve cloud, network, and infrastructure-related issues in a timely manner. • Drive cost optimization initiatives, resource efficiency, and performance improvements across cloud environments.

Role Description - Design, build, and maintain scalable cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Pulumi. - Develop, implement, and optimize CI/CD pipelines to enable efficient and reliable software delivery. - Ensure cloud infrastructure adheres to best practices for security, scalability, availability, and performance. - Automate infrastructure provisioning and deployment processes following DevOps best practices. - Develop and maintain monitoring, logging, and alerting systems using tools such as CloudWatch, Prometheus, Grafana, or ELK. - Collaborate closely with development and QA teams to ensure smooth and efficient cloud operations. - Actively contribute as part of a cross-functional Agile/Scrum team. - Troubleshoot and resolve cloud, network, and infrastructure-related issues in a timely manner. - Drive cost optimization initiatives, resource efficiency, and performance improvements across cloud environments. Qualifications - Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. - Master's degree in a relevant technical discipline is preferred. - 6–8 years of experience in Cloud Engineering, DevOps, Infrastructure Automation, or similar roles. - Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP); multi-cloud exposure is a strong advantage. - Strong understanding of cloud platforms and cloud-native architecture principles. - Proficiency in Infrastructure as Code (IaC) and automation tools. - Solid experience with containerization and orchestration technologies, such as Docker and Kubernetes. - Practical experience in building and managing CI/CD pipelines using tools like GitLab, GitHub Actions, Jenkins, or Azure DevOps. - Familiarity with microservices architecture, APIs, and distributed systems. - Strong command of Linux system administration. - Proficiency in scripting or programming languages such as Python, Bash, or JavaScript. - Good understanding of cloud networking concepts, including VPCs, DNS, load balancers, and VPNs. - Experience implementing cloud security best practices and compliance standards. - Strong analytical thinking, troubleshooting, and problem-solving skills. - Experience managing Kubernetes clusters (EKS, AKS, GKE) and exposure to serverless technologies (AWS Lambda, Azure Functions, Cloud Run) will be considered a plus. - Familiarity with monitoring and observability tools such as Prometheus, Grafana, Datadog, or Dynatrace, as well as cloud cost optimization / FinOps practices, is a plus. - Contributions to open-source projects and/or relevant cloud certifications (e.g., AWS Solutions Architect, Azure Solutions Architect, Google Associate Cloud Engineer) are an added advantage. Requirements - Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. - Master's degree in a relevant technical discipline is preferred. - 6–8 years of experience in Cloud Engineering, DevOps, Infrastructure Automation, or similar roles. - Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP); multi-cloud exposure is a strong advantage. - Strong understanding of cloud platforms and cloud-native architecture principles. - Proficiency in Infrastructure as Code (IaC) and automation tools. - Solid experience with containerization and orchestration technologies, such as Docker and Kubernetes. - Practical experience in building and managing CI/CD pipelines using tools like GitLab, GitHub Actions, Jenkins, or Azure DevOps. - Familiarity with microservices architecture, APIs, and distributed systems. - Strong command of Linux system administration. - Proficiency in scripting or programming languages such as Python, Bash, or JavaScript. - Good understanding of cloud networking concepts, including VPCs, DNS, load balancers, and VPNs. - Experience implementing cloud security best practices and compliance standards. - Strong analytical thinking, troubleshooting, and problem-solving skills. - Experience managing Kubernetes clusters (EKS, AKS, GKE) and exposure to serverless technologies (AWS Lambda, Azure Functions, Cloud Run) will be considered a plus. - Familiarity with monitoring and observability tools such as Prometheus, Grafana, Datadog, or Dynatrace, as well as cloud cost optimization / FinOps practices, is a plus. - Contributions to open-source projects and/or relevant cloud certifications (e.g., AWS Solutions Architect, Azure Solutions Architect, Google Associate Cloud Engineer) are an added advantage. Company Description