As a Sales Development Representative (Inside Sales) at our company, your primary focus will be on lead generation and qualification within the US enterprise market. Your role is crucial in driving pipeline growth by identifying key decision-makers across various industries and generating interest in AI-based solutions. Your responsibilities will include proactively identifying and reaching out to decision-makers in target industries using a combination of calls, emails, and social media for lead generation. You will also be responsible for tracking, nurturing, and qualifying leads to ensure a seamless handoff to the sales team for pipeline management. Additionally, you will serve as the initial point of contact for potential clients, creating strong initial engagement. It is important to maintain up-to-date knowledge of market trends and challenges in industries such as Healthcare, BFSI, Media & Telecom, Transportation, and Travel & Logistics. To excel in this role, you should have at least 5 years of experience in B2B lead generation or prospecting, particularly for US enterprise clients. You should have a proven track record of success in industries like Healthcare, BFSI, Media & Telecom, Transportation, or Travel & Logistics. Being tech-savvy with experience in CRM systems like HubSpot is essential, along with the ability to quickly learn new tools and platforms. Excellent written and verbal communication skills are necessary to initiate and build lasting relationships with clients. A strong work ethic, high motivation, self-drive, and goal-orientation are characteristics that will help you meet lead targets effectively. It would be advantageous if you have experience with Salesforce or other advanced CRM platforms, as well as prior experience in selling AI-based solutions. This position is based in Hyderabad.,
Inside Sales Reps with 4-10 years of Experience.
Experience : 12- 18 Yrs of experience as a Data Architect in complex, large-scale data environments. SSIS, Databricks Expertise : Strong hands-on experience working with SSIS, Databricks, including using Apache Spark for data processing and optimization. ETL Tools : Proficient with various ETL tools and frameworks such as Informatica, Talend, or SSIS or DataBricks Big Data Technologies: In-depth knowledge of big data processing frameworks like Spark, Flink, Hadoop, Kafka, etc. NoSQL/MongoDB: Expertise in working with NoSQL databases, especially MongoDB, for large-scale data storage, retrieval, and optimization. Gen AI/AIML Models : Familiarity with data consumption. Programming Skills: Proficient in SQL , Python or Java, Power shell for building data pipelines. SQL and NoSQL Proficiency: Strong knowledge of SQL and experience working with both relational databases and NoSQL databases like MongoDB. Data Modeling: Expertise in designing and implementing data models, including OLAP, OLTP, dimensional, and document-based models (NoSQL Data Reporting: Experience in integrating with Reporting platforms like Tableau, Qlik, etc Data warehousing: Data warehousing is a key part of ETL process, as it stores data from multiple sources in an organized manner and will be needed to build a repeatable ETL workflow to support many different data sources. Experience in building Datawarehouse, Datalakes in Snowflake. Redesign and refactor legacy custom ETL processes to reusable ETL workflows that can ingest diverse data sources to normalize data to standard JSON / XML output. Data Governance: Knowledge of data governance, security standards, and best practices for managing sensitive data. Version Control: Experience with Git or other version control systems for code management. Certification: Databricks certification, MongoDB certification, Snowflake SnowPro certification, or other relevant certifications in data engineering, cloud platforms (AWS, Azure or GCP or TKGI), or big data technologies. Soft Skills: Strong problem-solving skills, excellent communication, and the ability to work in a collaborative team environment. Analytical Mindset: Ability to translate business requirements into scalable, efficient, and reliable ETL solutions. Knowledge on AI/ML/GEN AI is desirable
Job Description: Cybersecurity Systems Architect – AI-Driven Security Platforms Location: Hyderabad Department: Architecture & Engineering Reports to: CTO / Head of Engineering Role Overview We are looking for a Cybersecurity Systems Architect with deep expertise in security infrastructure, enterprise defense systems, and advanced AI/ML technologies. This role is hands-on and highly technical — you will be responsible for designing and architecting next-generation cyber defense platforms that leverage AI agents, reasoning systems, and autonomous remediation workflows. The ideal candidate has extensive experience in building and scaling enterprise-grade security systems (SIEM, SOAR, XDR, IAM, Cloud Security) and can work closely with AI/ML teams to create autonomous, explainable, and resilient AI-powered security solutions. Key Responsibilities Architecture & System Design Architect the end-to-end AI-driven cybersecurity suite (SIEM/SOAR/XDR integrations, threat detection, response automation). Define system reference architectures , security models, and design blueprints for agentic AI integration into SOC workflows . Ensure scalability, resilience, and compliance of systems across cloud, hybrid, and on-prem infrastructures. Lead technical evaluations of data pipelines, detection models, and response automation frameworks. Cybersecurity Expertise Provide deep technical expertise in threat detection, SOC operations, endpoint protection, IAM, and cloud security. Architect integrations with existing enterprise tools (e.g., CrowdStrike, SentinelOne, Splunk, Palo Alto, Fortinet). Translate real-world attack vectors (APTs, zero-days, insider threats) into defensive AI-driven countermeasures. Evaluate security risks of autonomous AI agents and design guardrails, safety nets, and auditability mechanisms. At least one hyperscaler (AWS, Azure, or GCP) cyber security tools required. AI/ML Integration Partner with data scientists to design AI/agentic systems that can reason, learn, and adapt (LLMs, anomaly detection, reinforcement learning). Architect data pipelines for ingesting telemetry at scale (logs, EDR, NDR, cloud telemetry). Define standards for explainability and transparency of AI-driven remediation decisions. Leadership & Mentorship Act as the technical authority for all cybersecurity system design decisions. Mentor engineers and product managers on security best practices and architectural principles. Collaborate cross-functionally with AI researchers, product managers, and customer-facing teams . Qualifications Education / Background Bachelor’s or Master’s in Computer Science, Cybersecurity, or Systems Engineering . 10–12+ years in enterprise cybersecurity architecture, SOC design, or advanced security engineering . Core Expertise Security Architecture: Strong knowledge of SIEM, SOAR, XDR, EDR, IAM, CASB, Zero Trust, and cloud security architectures. System Design: Large-scale distributed systems, high-throughput data pipelines, secure integrations. Threat Landscape: Deep familiarity with adversary tactics (MITRE ATT&CK), advanced persistent threats, and red-team/blue-team scenarios. AI & Automation Hands-on understanding of AI/ML frameworks (LLMs, RLHF, anomaly detection, autonomous agents). Experience with security automation frameworks (SOAR, orchestration pipelines, playbooks). Strong interest or experience in agentic AI applied to cybersecurity . Certifications (Preferred) CISSP, CISM, or SABSA (Enterprise Security Architecture). Cloud Security certifications (AWS Security, Azure Security Architect, GCP Professional Cloud Security Engineer). Offensive/Defensive certs (OSCP, CEH, GIAC) a plus.