Top Tech Jobs & Startup Jobs

Manage full-cycle recruiting, including candidate sourcing, phone screening, interview scheduling, communications, applicant tracking, background checks, onboarding support, job fairs, and recruitment reporting. Maintain employee and HR records, support hiring events and advertising strategies, and follow employment laws and HR best practices. The role requires at least one year of recruiting or HR experience, strong communication and organizational skills, Microsoft Office proficiency, and the ability to work scheduled shifts.

Designs, implements, and optimizes AI-powered workflow automation solutions. Responsibilities include analyzing business processes, documenting current and future workflows, gathering requirements, integrating automation tools with business systems, supporting testing and deployment, monitoring performance metrics, troubleshooting issues, training users, and promoting automation best practices. The role collaborates with business and technical stakeholders to identify efficiency improvements and support digital transformation initiatives.

Performs accounting duties including accounts receivable, invoicing, payment application, journal entries, accounts payable, bank transactions, month-end close, and account reconciliations. Investigates and corrects discrepancies while ensuring financial reporting complies with GAAP and internal policies. The role collaborates across departments and requires strong organization, communication, attention to detail, and independent judgment.

Design, develop, deploy, and optimize Generative AI applications using LLMs and AI frameworks. Build scalable APIs, automate workflows, integrate foundation models with enterprise systems, and improve model performance through testing and experimentation. Implement monitoring, quality assurance, governance, security, compliance, documentation, and risk mitigation. Evaluate emerging technologies, support proofs of concept, and collaborate with product, engineering, and business teams.

Build and maintain Retrieval-Augmented Generation systems integrating large language models with enterprise knowledge. Responsibilities include designing ingestion, indexing, vector search, semantic retrieval, embedding pipelines, APIs, and scalable knowledge architectures. The role also involves optimizing retrieval quality and performance, monitoring systems, implementing governance and security controls, troubleshooting, documenting procedures, and evaluating emerging AI retrieval technologies. Candidates need Python, production software development, cloud, LLM, RAG, and information retrieval experience.

Manages financial operations for a BPO business, including financial statements, accounts payable and receivable, payroll, tax and reporting compliance, budgeting, forecasting, variance analysis, audits, and financial recordkeeping. Collaborates with leadership on financial planning and strategic decisions while maintaining accurate documentation and adherence to IFRS or GAAP standards.

Supports attorneys by conducting legal research, drafting contracts and litigation documents, organizing case files, tracking deadlines, preparing court materials, communicating with clients, and handling scheduling and correspondence. The role requires strong knowledge of legal terminology and processes, excellent organization and communication skills, attention to detail, confidentiality, and proficiency with Microsoft Office, legal research databases, and document management systems.

Annotates, labels, categorizes, validates, and quality-checks structured and unstructured data for AI model training. Maintains dataset accuracy, consistency, documentation, and version control while collaborating with AI engineers, data scientists, and quality teams. The role also supports annotation workflow management, guideline development, calibration exercises, error identification, and continuous process improvement.

Leads the architecture, development, optimization, deployment, and lifecycle management of enterprise machine learning systems. Establishes AI engineering standards, MLOps practices, data quality processes, model governance, security, and validation frameworks. Provides technical leadership, mentors engineers, evaluates emerging technologies, and supports AI transformation initiatives while partnering with data scientists, engineering, product, and business teams.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product requirements, priorities, success metrics, and business outcomes while coordinating engineering, AI, executives, and business stakeholders. Evaluates emerging AI technologies, supports responsible AI governance, manages feedback and adoption, and drives continuous product improvement.