Top Tech Jobs & Startup Jobs

Manage the full recruitment lifecycle for executive and leadership positions, including sourcing, talent mapping, candidate evaluation, interviews, and placement. Partner with senior leaders and hiring managers to understand workforce needs and succession plans. Maintain executive talent pipelines, provide market and compensation insights, monitor recruiting metrics, and deliver a positive candidate experience. The role requires executive search expertise, strong stakeholder management, strategic thinking, and familiarity with ATS and sourcing platforms.

Manage accounts receivable and payable, journal entries, bank and account reconciliations, month-end close, financial records, and discrepancy resolution. The role supports accurate GAAP-compliant reporting, budgeting, internal controls, and collaboration across business units. Candidates should have accounting experience, strong communication and organizational skills, and the ability to work independently in a fast-paced environment.

Leads the design, development, optimization, and governance of enterprise Retrieval-Augmented Generation platforms. Responsibilities include building retrieval and knowledge systems, improving semantic and vector search quality, integrating retrieval services with LLMs and AI applications, developing scalable APIs, ensuring security and compliance, monitoring performance, troubleshooting issues, evaluating emerging technologies, and mentoring engineering teams.

Labels, categorizes, validates, and quality-checks structured and unstructured data used to train AI and machine learning models. Maintains dataset accuracy, consistency, documentation, and version control while following detailed annotation guidelines. Collaborates with AI engineers, data scientists, and quality teams, identifies errors, provides process feedback, and supports continuous improvement of annotation workflows.

Annotate, label, classify, and validate structured and unstructured data for AI and machine learning training datasets. Review data quality, identify inconsistencies, maintain dataset documentation and version control, track workflow progress, and collaborate with AI trainers, engineers, data scientists, and quality teams. The role also contributes to improving annotation guidelines, processes, efficiency, and accuracy.

Conduct keyword research, competitive analysis, and technical SEO audits; optimize website pages, metadata, and on-page elements; support link building and search-optimized content; manage content calendars and keyword frameworks; monitor SEO KPIs, analyze trends, and produce performance reports. The role also requires staying current with search algorithm updates and collaborating with content and cross-functional teams.

Supports HR operations across employee relations, engagement, retention, training, workforce planning, compliance, HRIS maintenance, payroll audits, policy implementation, and process improvement. Partners with operations leaders, resolves workplace issues, maintains employee records, and ensures consistent application of HR policies. The role is full-time and on-site, requiring strong communication, organization, conflict resolution, and multitasking skills.

Designs and maintains Retrieval-Augmented Generation systems, including document ingestion, indexing, semantic search, vector databases, embedding pipelines, and LLM integrations. Develops APIs and scalable knowledge systems, optimizes retrieval accuracy and performance, monitors production environments, and implements governance and security controls. The role also evaluates emerging retrieval technologies, troubleshoots indexing issues, documents procedures, and collaborates with AI engineers and product teams.

Leads the strategy, roadmap, delivery, and continuous improvement of AI-powered products. Defines product vision, requirements, priorities, metrics, and success criteria while collaborating with executives, engineering, AI, data science, and business teams. Oversees product launches, adoption, performance optimization, stakeholder communication, and responsible AI governance. Requires strong product management, analytical, commercial, Agile, executive communication, and cross-functional leadership skills.

Designs and maintains Retrieval-Augmented Generation systems, including document ingestion, indexing, semantic and vector search, embeddings, and enterprise knowledge repositories. Integrates retrieval services with LLMs through APIs and scalable cloud-native architectures. Monitors accuracy, performance, security, governance, and data quality while troubleshooting systems and evaluating emerging retrieval technologies. Collaborates with AI engineers and product teams to deliver reliable, context-aware AI solutions.