AiStrike

Job Description: The next evolution of AI powered cyber defense is here. With the rise of cloud and modern technologies, organizations struggle with the vast amount of data and thereby security alerts generated by their existing security tools. Cyberattacks continue to get more sophisticated and harder to detect in the sea of alerts and false positives. According to the Forrester 2023 Enterprise Breach Benchmark Report, a security breach costs organizations an average of $3M and takes organizations over 200 days to investigate and respond. AiStrike’s platform aims at reducing the time to investigate and respond to threats by over 90%. Our approach is to leverage the power of AI and machine learning to adopt an attacker mindset to prioritize and automate cyberthreat investigation and response. The platform reduces alerts by 100:5 and provides detailed context and link analysis capabilities to investigate the alert. The platform also provides collaborative workflow and no code automation to cut down the time to respond to threats significantly. If you have the desire to join the next evolution of cyber defense, are willing to work hard and learn fast, and be part of building something special, this is the company for you. We are seeking a highly skilled and experienced hands-on Principal Software Engineer with over 10+ years of proven expertise in the field. As a Principal Architect, you will play a crucial role in leading the architecture, designing, and implementing scalable cloud solutions for our Cloud-native SaaS products. The ideal candidate will have significant experience and a strong background in object-oriented design and coding skills, with hands-on experience in Java and Python. Roles and Responsibilities: Manage overarching product/platform architecture, and technology selection and make sure that the design and development of all projects follow the architectural vision Design and architect scalable cloud solutions for Cloud-native SaaS development projects in line with the latest technology and practices Successfully communicate, evangelize, and implement the architectural vision across teams and products Design and coordinate projects of significant size and complexity Work with containerization technologies and orchestration software such as Kubernetes on cloud platforms like AWS and Azure. Develop and implement Microservices-based architecture using Java, SpringBoot, ReactJS, NextJS, and other relevant technologies. Implement secure design principles and practices, ensuring the integrity and confidentiality of our systems. Collaborate with cross-geography cross-functional teams to define and refine requirements and specifications. Deploy workloads at scale in AWS EKS/ECS environments and others as needed Create automation and use monitoring tools to efficiently build, deploy and support cloud implementations. Implement DevOps methodologies and tools for continuous integration and delivery. Utilize APM and Monitoring Tools like ELK, Splunk, Datadog, Dynatrace, and Appdynamics for cloud-scale monitoring. Work with potential customers to understand their environment. Provide technical leadership, architecture guidance, and mentorship to the teams. Have a clear focus on scale, cost, security, and maintainability. Stay updated on industry best practices, emerging technologies, and cybersecurity trends. Skills and Qualifications: 10+ years of overall experience in software development and architecture. In depth knowledge and experience in Cloud-native SaaS development and architecture. Proficient in Java, Python, RESTful APIs, API Gateway, Kafka, and Microservices communications. Experience with RDBMS and NoSQL databases (e.g., Neo4J, MongoDB, Redis). Experience in working with Graph databases like Neo4J. Expertise in containerization technologies (Docker) and Kubernetes. Hands-on experience with secure DevOps practices. Familiarity with Multi-Factor Authentication and Single Sign-On principles. Excellent verbal and written communication skills. Self-starter with strong organizational and problem-solving skills. Prior experience in deploying workloads at scale in AWS EKS/ECS/Fargate. Knowledge of Cloud-scale APM and Monitoring Tools (ELK, Splunk, Datadog, etc.). Previous experience in Cybersecurity products is desirable but not mandatory. Preferred: AWS Certified Solutions Architect – Professional or similar certification, including certifications on other cloud platforms. Commitment, team player, integrity and customer focus AiStrike is committed to providing equal employment opportunities. All qualified applicants and employees will be considered for employment and advancement without regard to race, color, religion, creed, national origin, ancestry, sex, gender, gender identity, gender expression, physical or mental disability, age, genetic information, sexual or affectional orientation, marital status, status regarding public assistance, familial status, military or veteran status or any other status protected by applicable law. Show more Show less

Senior Detection Engineer / Threat Hunter Overview The next evolution of AI-powered cyber defense is here. With the rise of cloud and modern technologies, organizations struggle with the vast amount of data and thereby security alerts generated by their existing security tools. Cyberattacks continue to get more sophisticated and harder to detect in the sea of alerts and false positives. According to the Forrester 2023 Enterprise Breach Benchmark Report, a security breach costs organizations an average of $3M and takes organizations over 200 days to investigate and respond. AiStrike’s platform aims to reduce the time to investigate and respond to threats by over 90%. Our approach is to leverage the power of AI and machine learning to adopt an attacker mindset to prioritize and automate cyber threat investigation and response. The platform reduces alerts by 100:5 and provides detailed context and link analysis capabilities to investigate the alert. The platform also provides collaborative workflow and no code automation to cut down the time to respond to threats significantly. We’re seeking a senior-level Detection Engineer and Threat Hunter with deep expertise in modern SIEMs and a strong focus on AI-augmented threat detection and investigation. In this role, you’ll design scalable, modular detection content using Sigma, KQL, and platform-specific query languages — while working with AI to automate detection tuning, threat hunting hypotheses, and investigation workflows across enterprise and cloud environments. Key Responsibilities Develop high-fidelity, AI-ready detection templates to build detection rules in Sigma, KQL, SPL, Lucene, etc., for Microsoft Sentinel, Chronicle, Splunk, and Elastic. Leverage AI-powered engines to prioritize, cluster, and tune detection content dynamically based on environment behavior and telemetry changes. Identify visibility and data coverage gaps across cloud, identity, EDR, and SaaS log sources; work cross-functionally to close them. Lead proactive threat hunts driven by AI-assisted hypotheses, anomaly detection, and known threat actor TTPs. Contribute to AI-enhanced detection-as-code pipelines, integrating rules into CI/CD workflows and feedback loops. Collaborate with SOC, threat intel, and AI/data science teams to continuously evolve detection efficacy and reduce alert fatigue. Participate in adversary emulation, purple teaming, and post-incident reviews to drive continuous improvement. Required Skills 5+ years of hands-on experience in detection engineering, threat hunting, or security operations. Expert-level knowledge of at least two major SIEM platforms: Microsoft Sentinel, Google Chronicle, Splunk, Elastic, or similar. Strong proficiency in detection rule languages (Sigma, KQL, SPL, Lucene) and mapping to MITRE ATT&CK. Experience using or integrating AI/ML for detection enrichment, alert correlation, or anomaly-based hunting. Familiarity with telemetry sources (EDR, cloud, identity, DNS, proxy) and techniques to enrich or normalize them. Ability to document, test, and optimize detection rules and threat hunt queries in a modular, scalable fashion. Strong communication skills and the ability to translate complex threat scenarios into automated, AI-ready detection logic. Nice to Have Experience integrating AI/ML platforms for security analytics, behavior baselining, or entity risk scoring. Familiarity with detection-as-code and GitOps workflows for rule development, testing, and deployment. Scripting knowledge (Python, PowerShell) for enrichment, custom detection logic, or automation. Experience with purple teaming tools like Atomic Red Team, SCYTHE, or Caldera. AiStrike is committed to providing equal employment opportunities. All qualified applicants and employees will be considered for employment and advancement without regard to race, color, religion, creed, national origin, ancestry, sex, gender, gender identity, gender expression, physical or mental disability, age, genetic information, sexual or affectional orientation, marital status, status regarding public assistance, familial status, military or veteran status or any other status protected by applicable law. Show more Show less

Sr Director/ VP AI & Machine Learning – Strategy Overview The next evolution of AI-powered cyber defense is here. With the rise of cloud and modern technologies, organizations struggle with the vast amount of data and thereby security alerts generated by their existing security tools. Cyberattacks continue to get more sophisticated and harder to detect in the sea of alerts and false positives. According to the Forrester 2023 Enterprise Breach Benchmark Report, a security breach costs organizations an average of $3M and takes organizations over 200 days to investigate and respond. AiStrike’s platform aims to reduce the time to investigate and respond to threats by over 90%. Our approach is to leverage the power of AI and machine learning to adopt an attacker mindset to prioritize and automate cyber threat investigation and response. The platform reduces alerts by 100:5 and provides detailed context and link analysis capabilities to investigate the alert. The platform also provides collaborative workflow and no code automation to cut down the time to respond to threats significantly. We are looking for a forward-thinking Leader for AI to define and lead the AI and ML strategy for our next-generation cybersecurity platform. This role sits at the intersection of data science, cybersecurity operations, and product innovation, responsible for transforming security telemetry into intelligent workflows, automated decisions, and self-improving systems. You will lead the vision and execution for how classification, clustering, correlation, and feedback loops are built into our AI-powered threat investigation and response engine. Your work will directly impact how analysts investigate alerts, how automation adapts over time, and how customers operationalize AI safely and effectively in high-stakes security environments. Key Responsibilities ● Define the AI Strategy & Roadmap: Own and drive the strategic direction for AI/ML across investigation, prioritization, alert triage, and autonomous response. ● Architect Feedback-Driven AI Systems: Design scalable feedback loops where analyst input, alert outcomes, and system performance continuously refine models. ● Operationalize ML for Security: Work with detection engineering, platform, and data teams to apply clustering, classification, and anomaly detection on massive datasets—logs, alerts, identities, cloud events—not images or media. ● Guide Complex Security Workflows: Translate noisy, high-volume telemetry into structured workflows powered by AI—spanning enrichment, correlation, and decisioning. ● Collaborate Across Functions: Partner with product managers, detection engineers, threat researchers, and ML engineers to define use cases, data needs, and modeling approaches. ● Ensure Explainability and Trust: Prioritize model transparency, accuracy, and control—enabling human-in-the-loop or override in high-risk environments. ● Lead AI Governance and Deployment Frameworks: Define policies, versioning, validation, and release processes for customer-safe AI usage in production environments. Requirements ● 10+ years of experience in data science, applied ML, or AI product leadership, with at least 3–5 years in cybersecurity, enterprise SaaS, or complex data domains. ● Demonstrated experience applying classification, clustering, correlation, and anomaly detection on structured/semi-structured data (e.g., logs, alerts, network events). ● Strong understanding of cybersecurity workflows: detection, investigation, triage, threat hunting, incident response, etc. ● Experience in building data feedback pipelines or reinforcement learning-like systems where user input improves future predictions or decisions. ● Proven ability to scale AI/ML systems across multi-tenant environments or customer-facing platforms. ● Familiarity with platforms such as Snowflake, Google Chronicle, Sentinel (KQL), or SIEM/SOAR tools is a strong plus. ● Exceptional communication and storytelling skills: able to communicate AI strategy to technical and executive stakeholders alike. ● Experience with security-specific ML tooling or frameworks (e.g., security data lakes, Sigma correlation engines, MITRE ATT&CK mapping). ● Prior work in multi-modal learning environments (signals from logs, identity, cloud infra, etc.). ● Deep familiarity with model evaluation, drift detection, and automated retraining in production settings. ● Exposure to or leadership in building agentic AI workflows or co-pilot-style assistant models in the security space. AiStrike is committed to providing equal employment opportunities. All qualified applicants and employees will be considered for employment and advancement without regard to race, color, religion, creed, national origin, ancestry, sex, gender, gender identity, gender expression, physical or mental disability, age, genetic information, sexual or affectional orientation, marital status, status regarding public assistance, familial status, military or veteran status or any other status protected by applicable law. Show more Show less

Senior Product Manager – AI-Powered Investigation & Response Content Overview We’re seeking a seasoned Senior Product Manager to lead the strategy and delivery of AI-driven threat investigation and response content within our next-gen AI investigation platform. This role is ideal for someone who has hands-on experience with detection logic (e.g., Sigma, KQL, YAML), but is now focused on building scalable pipelines and frameworks that feed AI-based workflows for automated investigation, prioritization, and response. You’ll be responsible for defining how threat signals, detections, and analyst actions are transformed into dynamic content that powers automated and guided investigations—integrated across cloud platforms and SOC environments. Key Responsibilities Own the Product Strategy for investigation and response content that supports AI-based decision-making and automation. Operationalize Content Pipelines to continuously deliver investigation and response content (e.g., decision trees, playbooks, enrichment steps) across customers via CI/CD. Standardize Content Frameworks to ensure structured, reusable, and extensible logic using formats like YAML, Sigma, and JSON. Collaborate with Detection & ML Teams to align investigation triggers, context enrichment, and response actions with AI models and logic engines. Map Detection to Investigation: Work with engineering and threat teams to define how signals from Snowflake, Google Chronicle, Sentinel (KQL), etc., are consumed and enriched in investigation workflows. Drive Feedback Loops: Define structures that enable AI to learn from analyst feedback, human-in-the-loop responses, and investigation outcomes. Ensure Coverage Across Platforms: Coordinate across cloud environments (AWS, Azure, GCP) as well as across products aligning to the same category - Firewalls, IAM, EDR/XDR etc to ensure that AI-driven content works consistently with telemetry from each source. Measure & Optimize content usage, accuracy, and performance across customer environments. Requirements 7–10 years in Product Management or a hybrid Detection Engineering/Content role, preferably in cloud security or threat detection/response. Experience working with or building detection content in Sigma, YAML, or KQL (Microsoft Sentinel). Familiarity with SIEM / data lakes such as Snowflake, Google Chronicle, ELK,Splunk, MS Sentinel or similar systems. Strong understanding of threat detection signals, cloud telemetry, and how they map to automated investigations and playbook-driven response. Demonstrated experience in operationalizing security content using Git-based workflows, CI/CD pipelines, and versioning best practices. Strong collaboration skills; ability to work cross-functionally with engineers, threat researchers, and AI/ML teams. Nice to Have Experience with AI/ML-based investigation platforms or decision engines for security operations. Familiarity with response frameworks like SOAR, XDR, or custom security automation platforms. Prior experience in building multi-tenant, content-driven platforms or working with MSSPs. Scripting skills (Python, Bash) or previous hands-on work automating security tasks. Security certifications (e.g., GCIA, GCTI, CISSP) or prior SOC/IR background. Show more Show less

As a Security Engineer Intern at our company, you will have the opportunity to utilize your strong Python scripting and SQL skills to enhance cybersecurity through AI-driven security solutions. Your main responsibilities will include automating security processes, developing YAML configurations, and assisting in analytical functions to improve our investigation and response capabilities. You will be expected to develop Python scripts for automating security analytics and response processes, as well as write SQL queries to extract and analyze security-related data from databases. Additionally, you will create and manage YAML configurations to streamline investigation workflows and support engineering and product teams by developing automation tools to detect, investigate, and respond to threats. To succeed in this role, you should have a strong background in Python scripting and SQL, along with a basic understanding of cybersecurity concepts such as threat detection, security operations, and log analysis. Familiarity with networking fundamentals like TCP/IP, DNS, firewalls, and VPNs, as well as knowledge of operating systems (Linux, Windows) and security best practices, will be beneficial. Moreover, experience working with YAML configurations for security tools and automation, coupled with an eagerness to learn about AI-driven cybersecurity and cloud security practices, are key qualifications for this position. Exposure to cloud security and investigation techniques, working with APIs and security tools like SIEM, CSPM, CNAPP, and knowledge of basic machine learning concepts in security are preferred skills that would be advantageous in this role. Stay updated on cybersecurity trends, including network security, cloud security, and AI-driven security, to ensure you are continuously improving your skills and knowledge in the field.,

We are seeking a highly motivated and talented Data Science Intern with specialized experience in Artificial Intelligence (AI) and Machine Learning (ML). As a Data Science Intern, you will have the opportunity to work on cutting-edge projects related to prompt engineering, large language model (LLM) training, and various ML capabilities such as prioritization, NLP-based classification, and clustering. This is an exciting opportunity to contribute to innovative solutions and gain hands-on experience in a dynamic and collaborative environment. Fill Application Form Roles And Responsibilities AI Prompt Engineering: Collaborate with the team to design and develop effective prompts for AI models. Experiment with different prompt strategies to enhance model performance and accuracy. Analyze and iterate on prompt engineering techniques to optimize model outputs. LLM Training Assist in the training and fine-tuning of large language models. Contribute to the development of training pipelines and workflows. Work on improving model efficiency, scalability, and resource utilization. Machine Learning Prioritization: Develop and implement algorithms for prioritizing tasks, data, or processes based on machine learning techniques. NLP-Based Classification: Build models for natural language processing-based classification tasks, ensuring high accuracy and robustness. Clustering: Utilize machine learning algorithms for data clustering to uncover patterns and relationships in large datasets. Collaboration And Communication Work closely with cross-functional teams to understand project requirements and objectives. Communicate effectively with team members and present findings in a clear and concise manner. Collaborate with other data scientists, engineers, and stakeholders to drive project success. Research And Innovation Stay updated on the latest advancements in AI and ML technologies. Contribute to the research and development of new methodologies to solve challenging problems. Propose and implement innovative solutions to enhance model performance and efficiency. Documentation Document code, methodologies, and experiment results for future reference. Create clear and comprehensive documentation for models, algorithms, and processes. Qualifications Currently pursuing a degree in Computer Science, Data Science, or a related field. Strong programming skills in languages such as Python, and experience with relevant libraries and frameworks. Familiarity with AI and ML concepts, including natural language processing, deep learning, and model training. Knowledge of prompt engineering techniques and large language models. Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Ability to work independently and as part of a team. If you are an accomplished and skilled Data Scientist with experience in large language models, frameworks such as OpenAI, Hugging Face, and Langchain, and the ability to review, improve, and leverage Transformers, we encourage you to apply. We offer a competitive salary, excellent benefits, and a dynamic work environment where you can make a significant impact on the development of cutting-edge technology and be a part of the next growth in Cybersecurity.

We are seeking a highly skilled and motivated Machine Learning Engineer with a strong background in machine learning, and data science, and a passion for solving problems related to prioritization, classification, and clustering in the evolving field of cybersecurity. In this role, you will play a critical part in building and deploying machine learning models to enhance our prioritization and recommendation systems to improve alert fatigue. Your work will have a direct impact on optimizing processes and decision-making within our organization. Fill Application Form Key Responsibilities Data Preparation: Collect, preprocess, and clean data to make it suitable for machine learning tasks. Work closely with data engineers to access and transform data as needed. Model Development: Design, implement, and optimize machine learning models, including traditional techniques such as autoregressive (AR), Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), Exponential Smoothing (ES), as well as advanced algorithms like XGBoost, Prophet, LSTM (Deep Learning), DeepAR, N-BEATS, and Temporal Fusion Transformer (Google), to solve prioritization and classification problems effectively. Feature Engineering: Conduct comprehensive feature engineering to enhance model performance and interpretability. Leverage domain knowledge and innovative techniques to create informative features. Model Training and Evaluation: Train and evaluate machine learning models using rigorous methodologies and performance metrics. Fine-tune model parameters and hyperparameters to achieve optimal results. Hyperparameter Tuning: Optimize model hyperparameters to improve performance and adapt models to evolving data patterns. Deployment: Deploy machine learning models into production environments, ensuring they integrate seamlessly with existing systems and are scalable. Model Monitoring: Establish monitoring systems to track model performance over time and address any issues that may arise. Collaboration: Collaborate with cross-functional teams, including data scientists, data engineers, software engineers, and business stakeholders, to understand their requirements and provide effective solutions. Documentation: Document the entire machine learning pipeline, model specifications, and results for clear communication and knowledge sharing. Requirements Bachelor's degree or higher in computer science, machine learning, data science, or a related field. Solid understanding of statistical methods and machine learning algorithms. Proven experience as a Machine Learning Engineer with a focus on ranking, prioritization, classification, and clustering tasks. Strong experience in working with labeled data to build machine-learning models. Proficiency in using machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Experience with data preprocessing, feature engineering, and data visualization. Strong programming skills in Python. 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). Proven track record of developing and deploying live production systems as part of a product team for at least 3 years. Experience leading the development and deployment of products or systems throughout the product cycle from ideation to shipping. Expertise in traditional machine learning techniques (AR, ARIMA, SARIMA, ES), deep learning architectures (LSTM, DeepAR, N-BEATS, Temporal Fusion Transformer), and ensemble methods (XGBoost). Deep understanding of machine learning algorithms and model evaluation techniques. Knowledge of deep learning techniques and neural networks is a plus. Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker). Strong problem-solving and analytical skills. Excellent communication and teamwork skills. Experience with natural language processing (NLP) and text classification is a bonus. Knowledge of reinforcement learning or recommendation systems is a plus.

We are seeking a highly skilled and experienced Software Architect with over 12+ years of proven expertise in the field. As a Software Architect, you will play a crucial role in designing and implementing scalable solutions for our Cloud-native SaaS development projects. The ideal candidate will have a strong background in object-oriented design and coding skills, with hands-on experience in Java and Python. Fill Application Form Role Design and architect scalable solutions for Cloud-native SaaS development projects. Work with containerization technologies and orchestration software such as Kubernetes on cloud platforms like AWS and Azure. Develop and implement Microservices-based architecture using Java, SpringBoot, ReactJS, NextJS, and other relevant technologies. Implement secure design principles and practices, ensuring the integrity and confidentiality of our systems. Collaborate with cross-functional teams to define and refine requirements and specifications. Deploy workloads at scale in AWS EKS/ECS environments. Utilize Multi-Factor Authentication and Single Sign-On (OAuth, SAML) for enhanced security. Work with various AWS services such as EC2, EKS, and others as needed. Implement DevOps methodologies and tools for continuous integration and delivery. Utilize APM and Monitoring Tools like ELK, Splunk, Datadog, Dynatrace, and Appdynamics for cloud-scale monitoring. Stay updated on industry best practices, emerging technologies, and cybersecurity trends. Requirements 12+ years of overall experience in software development and architecture. Certified AWS Architect - AWS Certified Solutions Architect Professional. Strong knowledge and experience in Cloud-native SaaS development and architecture. Proficient in Java, Python, RESTful APIs, API Gateway, Kafka, and Microservices communications. Experience with RDBMS and NoSQL databases (e.g., Neo4J, MongoDB, Redis). Experience in working with Graph databases like Neo4J. Expertise in containerization technologies (Docker) and Kubernetes. Hands-on experience with secure DevOps practices. Familiarity with Multi-Factor Authentication and Single Sign-On principles. Excellent verbal and written communication skills. Self-starter with strong organizational and problem-solving skills. Prior experience in deploying workloads at scale in AWS EKS/ECS/Fargate. Knowledge of Cloud-scale APM and Monitoring Tools (ELK, Splunk, Datadog, etc.). Previous experience in Cybersecurity products is desirable but not mandatory. If you are a highly skilled Software Architect looking to make a significant impact in the development of innovative and secure cloud solutions, we invite you to apply and join our dynamic team.

We are seeking a skilled and highly motivated Software Development Engineer in Test (SDET) to join our dynamic team. The ideal candidate will possess strong experience in Python, automation, API automation, and functional testing. They will be responsible for designing and implementing automated tests, performing system and integration tests, and working with various modern technologies such as microservices, AWS, Kafka, Redis, Neo4j, and DevOps practices. Fill Application Form Key Responsibilities Test Automation: Design, develop, and maintain automated test scripts using Python. Implement and manage automated testing for APIs, functional tests, and microservices. Execute automated tests and analyze results to identify defects and ensure quality. System And Integration Testing Perform thorough system and integration tests to ensure the end-to-end quality of the software. Develop and execute test cases, scripts, plans, and procedures (manual and automated). Test Framework Development Design and maintain test frameworks to improve the efficiency and effectiveness of testing. Collaborate with development teams to integrate automated tests into the continuous integration and delivery pipeline. Cloud And Infrastructure Utilize AWS cloud services to deploy, manage, and test applications. Implement and manage microservices testing and ensure their reliability. DevOps Practices Work closely with DevOps teams to integrate automated tests into the CI/CD pipeline. Ensure smooth execution of Build Acceptance Tests (BAT) runs. Database And Messaging Use Kafka for messaging and event streaming in tests. Implement tests involving Redis and Neo4j databases to ensure data integrity and performance. Collaboration And Documentation Collaborate with cross-functional teams to define testing requirements and ensure coverage. Document test strategies, plans, and results thoroughly. Qualifications Education: Bachelor’s degree in Computer Science, Engineering, or a related field. Experience: Proven track record in system and integration tests, with hands-on experience in the following areas: Automation and Scripting: Proficient in Python for test automation. API Automation: Strong experience in API testing and automation tools. Functional Testing: Deep understanding of functional testing principles and practices. Microservices: Experience with testing microservices architectures. Cloud Services: Proficiency in AWS cloud services. Messaging Systems: Knowledge of Kafka for messaging. Databases: Experience with Redis and Neo4j. DevOps: Familiarity with CI/CD pipelines and DevOps practices. Test Frameworks: Experience in designing and maintaining test automation frameworks. Skills Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Attention to detail and commitment to quality. Ability to work in a fast-paced, agile environment. Preferred Qualifications Experience with additional programming languages and testing tools. Knowledge of performance testing and security testing practices.

Are you a seasoned UI Developer with a flair for design and a passion for cutting-edge technology? Join our dynamic team as a Senior UI Developer, where your expertise in UI development and design will be crucial in enhancing website usability and crafting exceptional user experiences. In this pivotal role, you'll engage in coding, maintaining the visual appeal of web applications, and ensuring intuitive interfaces. Your analytical skills will help us continuously improve functionality by understanding user behaviors and patterns. We’re looking for someone with a deep passion for user satisfaction, combined with advanced proficiency in web application development and design. If you excel in problem-solving and innovative thinking, we want you on our team. Fill Application Form Role And Responsibilities Design and develop cutting-edge user interfaces, enhancing visual and interactive elements for a seamless user experience. Utilise NextJS to build and optimize high-performance web applications. Manage the full UI software development lifecycle from initial concept through deployment and ongoing maintenance. Oversee post-deployment updates and manage UI applications through their entire lifecycle. Conduct automated testing, providing insightful feedback and ensuring high quality throughout development. Lead and mentor development teams, collaborating across projects to drive excellence. Apply strong design skills to create visually compelling and user-centric interfaces. Qualifications And Skills Expert-level proficiency in ReactJS and NextJS is essential, with strong experience in JavaScript (ES6+), HTML, and CSS. Experience with TypeScript is a significant advantage. Proven experience in integrating web services (e.g., REST APIs). Skilled in web application performance testing and monitoring. Hands-on experience with UI visualizations and graph libraries like Highcharts and React Flow or RappidJs. Proficient in Test-Driven Development (TDD) with a track record of writing unit and integration tests for UI components using Cypress or Playwright. Strong attention to design details, with a focus on achieving pixel-perfect UIs. Strong design skills with an in-depth understanding of UI design principles, patterns, and best practices. Experience defining and parsing data interchange formats with backend services (JSON, XML). Knowledge of RestAPIs or backend development is a bonus. Strong capability to maintain high delivery quality across projects, including code, planning, and estimates. Excellent knowledge of component design patterns, with outstanding problem-solving and communication skills. Ability to thrive in a fast-paced, collaborative environment. Minimum of 4 years of UI development experience, including building responsive web pages or applications at an enterprise level. Join our team to drive innovation in graphical user experiences and graph-based visualizations within the cybersecurity domain. Leverage your UI development and design expertise to make a significant impact, inspire growth, and contribute to cutting-edge technology. We offer a competitive salary, excellent benefits, and a dynamic work environment where you can play a key role in shaping the future of cybersecurity. Apply now to be part of our next wave of growth.

As a Software Development Engineer in Test (SDET) at our company, you will play a crucial role in ensuring the quality and reliability of our software products. Your responsibilities will include: - Test Automation: - Design, develop, and maintain automated test scripts using Python. - Implement and manage automated testing for APIs, functional tests, and microservices. - Execute automated tests and analyze results to identify defects and ensure quality. - System And Integration Testing: - Perform thorough system and integration tests to ensure the end-to-end quality of the software. - Develop and execute test cases, scripts, plans, and procedures (manual and automated). - Test Framework Development: - Design and maintain test frameworks to improve the efficiency and effectiveness of testing. - Collaborate with development teams to integrate automated tests into the continuous integration and delivery pipeline. - Cloud And Infrastructure: - Utilize AWS cloud services to deploy, manage, and test applications. - Implement and manage microservices testing and ensure their reliability. - DevOps Practices: - Work closely with DevOps teams to integrate automated tests into the CI/CD pipeline. - Ensure smooth execution of Build Acceptance Tests (BAT) runs. - Database And Messaging: - Use Kafka for messaging and event streaming in tests. - Implement tests involving Redis and Neo4j databases to ensure data integrity and performance. - Collaboration And Documentation: - Collaborate with cross-functional teams to define testing requirements and ensure coverage. - Document test strategies, plans, and results thoroughly. Qualifications: - Education: Bachelors degree in Computer Science, Engineering, or a related field. - Experience: Proven track record in system and integration tests, with hands-on experience in areas such as Automation and Scripting, API Automation, Functional Testing, Microservices, Cloud Services, Messaging Systems, Databases, DevOps, and Test Frameworks. Skills: - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Attention to detail and commitment to quality. - Ability to work in a fast-paced, agile environment. Preferred Qualifications: - Experience with additional programming languages and testing tools. - Knowledge of performance testing and security testing practices.,

We are seeking a highly skilled and motivated Machine Learning Engineer with a strong background in machine learning, and data science, and a passion for solving problems related to prioritization, classification, and clustering in the evolving field of cybersecurity. In this role, you will play a critical part in building and deploying machine learning models to enhance our prioritization and recommendation systems to improve alert fatigue. Your work will have a direct impact on optimizing processes and decision-making within our organization. Fill Application Form Key Responsibilities Data Preparation: Collect, preprocess, and clean data to make it suitable for machine learning tasks. Work closely with data engineers to access and transform data as needed. Model Development: Design, implement, and optimize machine learning models, including traditional techniques such as autoregressive (AR), Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), Exponential Smoothing (ES), as well as advanced algorithms like XGBoost, Prophet, LSTM (Deep Learning), DeepAR, N-BEATS, and Temporal Fusion Transformer (Google), to solve prioritization and classification problems effectively. Feature Engineering: Conduct comprehensive feature engineering to enhance model performance and interpretability. Leverage domain knowledge and innovative techniques to create informative features. Model Training and Evaluation: Train and evaluate machine learning models using rigorous methodologies and performance metrics. Fine-tune model parameters and hyperparameters to achieve optimal results. Hyperparameter Tuning: Optimize model hyperparameters to improve performance and adapt models to evolving data patterns. Deployment: Deploy machine learning models into production environments, ensuring they integrate seamlessly with existing systems and are scalable. Model Monitoring: Establish monitoring systems to track model performance over time and address any issues that may arise. Collaboration: Collaborate with cross-functional teams, including data scientists, data engineers, software engineers, and business stakeholders, to understand their requirements and provide effective solutions. Documentation: Document the entire machine learning pipeline, model specifications, and results for clear communication and knowledge sharing. Requirements Bachelor's degree or higher in computer science, machine learning, data science, or a related field. Solid understanding of statistical methods and machine learning algorithms. Proven experience as a Machine Learning Engineer with a focus on ranking, prioritization, classification, and clustering tasks. Strong experience in working with labeled data to build machine-learning models. Proficiency in using machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Experience with data preprocessing, feature engineering, and data visualization. Strong programming skills in Python. 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). Proven track record of developing and deploying live production systems as part of a product team for at least 3 years. Experience leading the development and deployment of products or systems throughout the product cycle from ideation to shipping. Expertise in traditional machine learning techniques (AR, ARIMA, SARIMA, ES), deep learning architectures (LSTM, DeepAR, N-BEATS, Temporal Fusion Transformer), and ensemble methods (XGBoost). Deep understanding of machine learning algorithms and model evaluation techniques. Knowledge of deep learning techniques and neural networks is a plus. Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker). Strong problem-solving and analytical skills. Excellent communication and teamwork skills. Experience with natural language processing (NLP) and text classification is a bonus. Knowledge of reinforcement learning or recommendation systems is a plus.

We are seeking a highly motivated and talented Data Science Intern with specialized experience in Artificial Intelligence (AI) and Machine Learning (ML). As a Data Science Intern, you will have the opportunity to work on cutting-edge projects related to prompt engineering, large language model (LLM) training, and various ML capabilities such as prioritization, NLP-based classification, and clustering. This is an exciting opportunity to contribute to innovative solutions and gain hands-on experience in a dynamic and collaborative environment. Fill Application Form Roles And Responsibilities AI Prompt Engineering: Collaborate with the team to design and develop effective prompts for AI models. Experiment with different prompt strategies to enhance model performance and accuracy. Analyze and iterate on prompt engineering techniques to optimize model outputs. LLM Training Assist in the training and fine-tuning of large language models. Contribute to the development of training pipelines and workflows. Work on improving model efficiency, scalability, and resource utilization. Machine Learning Prioritization: Develop and implement algorithms for prioritizing tasks, data, or processes based on machine learning techniques. NLP-Based Classification: Build models for natural language processing-based classification tasks, ensuring high accuracy and robustness. Clustering: Utilize machine learning algorithms for data clustering to uncover patterns and relationships in large datasets. Collaboration And Communication Work closely with cross-functional teams to understand project requirements and objectives. Communicate effectively with team members and present findings in a clear and concise manner. Collaborate with other data scientists, engineers, and stakeholders to drive project success. Research And Innovation Stay updated on the latest advancements in AI and ML technologies. Contribute to the research and development of new methodologies to solve challenging problems. Propose and implement innovative solutions to enhance model performance and efficiency. Documentation Document code, methodologies, and experiment results for future reference. Create clear and comprehensive documentation for models, algorithms, and processes. Qualifications Currently pursuing a degree in Computer Science, Data Science, or a related field. Strong programming skills in languages such as Python, and experience with relevant libraries and frameworks. Familiarity with AI and ML concepts, including natural language processing, deep learning, and model training. Knowledge of prompt engineering techniques and large language models. Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Ability to work independently and as part of a team. If you are an accomplished and skilled Data Scientist with experience in large language models, frameworks such as OpenAI, Hugging Face, and Langchain, and the ability to review, improve, and leverage Transformers, we encourage you to apply. We offer a competitive salary, excellent benefits, and a dynamic work environment where you can make a significant impact on the development of cutting-edge technology and be a part of the next growth in Cybersecurity.

Are you a seasoned UI Developer with a flair for design and a passion for cutting-edge technology Join our dynamic team as a Senior UI Developer, where your expertise in UI development and design will be crucial in enhancing website usability and crafting exceptional user experiences. In this pivotal role, you'll engage in coding, maintaining the visual appeal of web applications, and ensuring intuitive interfaces. Your analytical skills will help us continuously improve functionality by understanding user behaviors and patterns. We're looking for someone with a deep passion for user satisfaction, combined with advanced proficiency in web application development and design. If you excel in problem-solving and innovative thinking, we want you on our team. Fill Application Form Role And Responsibilities Design and develop cutting-edge user interfaces, enhancing visual and interactive elements for a seamless user experience. Utilise NextJS to build and optimize high-performance web applications. Manage the full UI software development lifecycle from initial concept through deployment and ongoing maintenance. Oversee post-deployment updates and manage UI applications through their entire lifecycle. Conduct automated testing, providing insightful feedback and ensuring high quality throughout development. Lead and mentor development teams, collaborating across projects to drive excellence. Apply strong design skills to create visually compelling and user-centric interfaces. Qualifications And Skills Expert-level proficiency in ReactJS and NextJS is essential, with strong experience in JavaScript (ES6+), HTML, and CSS. Experience with TypeScript is a significant advantage. Proven experience in integrating web services (e.g., REST APIs). Skilled in web application performance testing and monitoring. Hands-on experience with UI visualizations and graph libraries like Highcharts and React Flow or RappidJs. Proficient in Test-Driven Development (TDD) with a track record of writing unit and integration tests for UI components using Cypress or Playwright. Strong attention to design details, with a focus on achieving pixel-perfect UIs. Strong design skills with an in-depth understanding of UI design principles, patterns, and best practices. Experience defining and parsing data interchange formats with backend services (JSON, XML). Knowledge of RestAPIs or backend development is a bonus. Strong capability to maintain high delivery quality across projects, including code, planning, and estimates. Excellent knowledge of component design patterns, with outstanding problem-solving and communication skills. Ability to thrive in a fast-paced, collaborative environment. Minimum of 4 years of UI development experience, including building responsive web pages or applications at an enterprise level. Join our team to drive innovation in graphical user experiences and graph-based visualizations within the cybersecurity domain. Leverage your UI development and design expertise to make a significant impact, inspire growth, and contribute to cutting-edge technology. We offer a competitive salary, excellent benefits, and a dynamic work environment where you can play a key role in shaping the future of cybersecurity. Apply now to be part of our next wave of growth.

We are seeking a skilled and highly motivated Software Development Engineer in Test (SDET) to join our dynamic team. The ideal candidate will possess strong experience in Python, automation, API automation, and functional testing. They will be responsible for designing and implementing automated tests, performing system and integration tests, and working with various modern technologies such as microservices, AWS, Kafka, Redis, Neo4j, and DevOps practices. Fill Application Form Key Responsibilities Test Automation: Design, develop, and maintain automated test scripts using Python. Implement and manage automated testing for APIs, functional tests, and microservices. Execute automated tests and analyze results to identify defects and ensure quality. System And Integration Testing Perform thorough system and integration tests to ensure the end-to-end quality of the software. Develop and execute test cases, scripts, plans, and procedures (manual and automated). Test Framework Development Design and maintain test frameworks to improve the efficiency and effectiveness of testing. Collaborate with development teams to integrate automated tests into the continuous integration and delivery pipeline. Cloud And Infrastructure Utilize AWS cloud services to deploy, manage, and test applications. Implement and manage microservices testing and ensure their reliability. DevOps Practices Work closely with DevOps teams to integrate automated tests into the CI/CD pipeline. Ensure smooth execution of Build Acceptance Tests (BAT) runs. Database And Messaging Use Kafka for messaging and event streaming in tests. Implement tests involving Redis and Neo4j databases to ensure data integrity and performance. Collaboration And Documentation Collaborate with cross-functional teams to define testing requirements and ensure coverage. Document test strategies, plans, and results thoroughly. Qualifications Education: Bachelor's degree in Computer Science, Engineering, or a related field. Experience: Proven track record in system and integration tests, with hands-on experience in the following areas: Automation and Scripting: Proficient in Python for test automation. API Automation: Strong experience in API testing and automation tools. Functional Testing: Deep understanding of functional testing principles and practices. Microservices: Experience with testing microservices architectures. Cloud Services: Proficiency in AWS cloud services. Messaging Systems: Knowledge of Kafka for messaging. Databases: Experience with Redis and Neo4j. DevOps: Familiarity with CI/CD pipelines and DevOps practices. Test Frameworks: Experience in designing and maintaining test automation frameworks. Skills Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Attention to detail and commitment to quality. Ability to work in a fast-paced, agile environment. Preferred Qualifications Experience with additional programming languages and testing tools. Knowledge of performance testing and security testing practices.