About the Role: We are seeking a results-driven and relationship-focused Account Manager with experience in US IT staffing to manage and grow key client accounts. You will be the primary liaison between our clients and our internal recruiting team, ensuring high-quality delivery and client satisfaction. This is a fully remote role with a high impact on revenue growth and client retention. Key Responsibilities: Manage existing client accounts in the US IT staffing domain, ensuring high levels of satisfaction and consistent communication. Understand client requirements and coordinate with the recruiting team to ensure timely and quality submissions. Build strong relationships with hiring managers and decision-makers. Identify opportunities for account growth through up-selling, cross-selling, and new job requisitions. Ensure service level agreements (SLAs) are met and proactively address any issues or delays. Maintain and track KPIs, reporting regularly on account performance. Stay current with market trends, technology skill demands, and industry best practices. Strong ability to build rapport and establish credibility with senior-level decision-makers. Self-motivated, results-oriented, and highly driven to exceed targets. Proven ability to work independently and manage your own sales pipeline. Requirements: 7+ years of experience as an Account Manager in the US IT staffing industry . Solid understanding of IT technologies and staffing lifecycle. Strong communication, negotiation, and relationship-building skill Responsible for both maintaining existing client relationships and acquiring new clients Ability to work independently in a fast-paced, remote environment. Familiarity with ATS systems, job boards, and sourcing tool

AI/ML engineer or GenAI developer who will leverage Amazon Bedrock to build and optimize intelligent systems for automated email organization, with a strong emphasis on prompt engineering, collaboration, testing, and adherence to best practices. Develops and fine-tunes Bedrock-based GenAI models for email categorization Implements prompt engineering techniques for accurate email processing Collaborates with data engineers to optimize email categorization workflows Conducts testing to refine prompt structures and improve model responses Enables compliance with AI governance and security best practices Works with business users to align AI-generated responses with organizational needs