Top Tech Jobs & Startup Jobs

Designs, deploys, and operates secure, resilient Azure cloud platforms for production workloads. Responsibilities include Azure architecture, infrastructure as code, automation, security hardening, cost optimization, observability, AKS operations, CI/CD, troubleshooting, and compliance. The engineer partners with application development, security, and SRE teams to deliver scalable cloud-native solutions. Preferred experience includes Azure certifications, hybrid or multi-cloud environments, service mesh technologies, FinOps, and regulated environments.

Define and lead organizational strategies, patterns, and tooling for prompts, agentic workflows, and LLM application architectures. Ship production LLM-powered products, build evaluation frameworks for non-deterministic systems, apply responsible AI principles, mentor engineers, and influence technical direction. The role also involves retrieval-augmented generation, embeddings, vector databases, multi-agent architectures, tool-use systems, fine-tuning, and enterprise integrations.

Design, build, and operate large-scale distributed backend systems and high-throughput services. Responsibilities include architecture, data partitioning, resilient APIs, event-driven systems, performance optimization, observability, incident response, technical documentation, mentoring, and collaboration with SRE and platform teams to improve reliability and reduce operational toil.

Design, develop, and integrate production robotics software across perception, localization, mapping, motion planning, control, behavior, sensor fusion, and real-time systems. Build ROS-based solutions, simulation environments, safety mechanisms, and hardware integrations. Conduct field testing, document system architecture and operations, collaborate with multidisciplinary teams, evaluate robotics technologies, and mentor engineers.

Designs, develops, tests, deploys, monitors, and supports enterprise integrations connecting Oracle Cloud Applications, on-premises Oracle systems, and third-party platforms. The role owns the full integration lifecycle and requires expertise in Oracle Integration Cloud, Visual Builder, APIs, REST/SOAP services, security standards, scripting, SQL, and Oracle data models. Responsibilities also include troubleshooting, documentation, integration migration, and collaboration across technical teams.

Designs and builds firmware, software tooling, and infrastructure supporting semiconductor design, verification, manufacturing, and post-silicon validation. Partners with hardware and EDA teams, develops low-level hardware-software solutions, builds cloud, grid, and HPC infrastructure, automates workflows, manages design data pipelines, troubleshoots complex issues, reviews designs and code, and mentors junior engineers.

Build low-latency trading, pricing, risk, market-data, backtesting, and analytics systems for fintech applications. Translate quantitative models into production software, optimize performance, implement risk and P&L attribution tools, support compliance reporting, and ensure observability, auditability, and operational reliability. Collaborate with quants, traders, and risk officers; lead incident response, document systems, review designs, and mentor junior engineers.

Develop and enhance SAP Fiori and UI5 applications across desktop, tablet, and mobile platforms. Own the full development lifecycle, collaborate with functional consultants, ABAP developers, and UX teams, and apply SAP Fiori guidelines, OData, accessibility, performance, authentication, and clean architecture principles. Deploy applications to ABAP frontend and BTP runtimes while supporting enterprise usability, maintainability, documentation, and business goals.

Design, develop, deploy, monitor, and support enterprise integrations on the Dell Boomi AtomSphere platform. Build connectors, data maps, APIs, secure authentication, event-driven workflows, and CI/CD pipelines. Manage Atom and Molecule runtimes, migrate legacy integrations, optimize performance, implement monitoring and documentation, and mentor junior developers. Collaborate with architects, application teams, integration partners, and business stakeholders to deliver reliable, scalable solutions.

Design, build, and operate reliable, high-performance production inference platforms for large machine learning models. Responsibilities include request routing, batching, caching, autoscaling, GPU utilization, observability, performance engineering, capacity planning, and balancing latency, throughput, cost, and quality. The role requires distributed systems expertise, experience with LLM inference frameworks, cloud and Kubernetes operations, production incident response, and support for scalable AI services.