Top Tech Jobs & Startup Jobs

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Lead the transformation of a profitable legal services company into an AI-native consumer law platform. Own the product and technology roadmap, build AI workflows across practice areas, improve the client portal, support law firm acquisitions, and hire and develop engineering, product, design, and data teams. The CTO will remain hands-on with coding while setting priorities and scaling the platform.

Build and deploy AI-powered software, full-stack applications, integrations, data pipelines, and automation for business processes. Partner with sales, finance, supply chain, production, and product teams to identify opportunities, launch measurable improvements, and own systems through testing, monitoring, documentation, training, and support. Establish engineering practices and connect ERP, accounting, commerce, shipping, spreadsheet, and plant data systems.

Leads and grows a distributed software engineering team building a scalable cloud data and analytics platform. Owns architecture, data modeling, technical delivery, roadmaps, product collaboration, agile planning, quality standards, security alignment, vendor relationships, and engineering KPIs. The role remains hands-on with coding, code reviews, documentation, data architecture, deployment, and development of SaaS data products using Azure or AWS, Microsoft Fabric or Snowflake, and Power BI.

Build and operate end-to-end agentic AI products from initial concept through production and product-market fit. Responsibilities include developing agents, retrieval and orchestration systems, integrating tools, shaping product direction with design and product partners, hardening systems after launch, and creating reusable engineering primitives. The role requires entrepreneurial ownership, production AI experience, strong engineering judgment, and the ability to work effectively with technical and commercial stakeholders.

Leads multiple engineering teams delivering AI-powered data connectivity solutions. Owns execution, delivery, technical direction, operational reliability, and cross-team coordination. Develops engineering talent through coaching, hiring, and performance management while partnering with Product and Engineering leadership on priorities and organizational planning. Guides architecture, cloud-native development, incident response, SLOs, and AI-assisted software development practices. Requires strong Java/Kotlin expertise, cloud architecture experience, and technical judgment across distributed systems.

Design, develop, test, maintain, and support enterprise software applications, APIs, services, integrations, and user-facing functionality. Translate requirements into technical designs, write maintainable code, participate in Agile planning and code reviews, troubleshoot production issues, and collaborate with analysts, QA, architects, and operations teams. Contribute to automated testing, technical documentation, production support, and continuous engineering improvement.

Develop secure, scalable, production-ready AI applications, services, and APIs. Integrate machine-learning and generative AI models into enterprise systems, build data and retrieval workflows, develop prompts, and implement testing, monitoring, logging, and evaluation. Collaborate with product, data, platform, and engineering teams while applying security, privacy, responsible-AI, and governance practices. Troubleshoot issues, document technical designs, participate in code reviews and Agile ceremonies, and support continuous improvement.

Lead end-to-end development of an AI-driven decision-support system for multi-sensor data. Responsibilities include building data ingestion and fusion pipelines, training and deploying supervised and unsupervised ML models, optimizing near-real-time inference, creating GPU-accelerated dashboards, integrating modular containerized systems, and supporting secure deployment and testing. The role works directly with the founder, owns technical delivery autonomously, and collaborates with subcontractors on human factors, model validation, and security auditing.

Manage and grow a product engineering team at a remote cloud cost-management software company. Lead prioritization, delivery, quality standards, recruiting, and cross-functional collaboration with product, design, and leadership. Help engineers ship customer-focused features spanning spend management, interfaces, data pipelines, visualizations, and application performance. Coach engineers, remove blockers, promote ownership, and guide tradeoffs between velocity and quality.