Top Tech Jobs & Startup Jobs

Design, develop, and deliver software components, APIs, microservices, and UIs; integrate AI/ML features; implement CI/CD, automated testing, IaC, and containerized cloud deployments; monitor production, troubleshoot issues, and mentor junior engineers.

Lead technical vision and architecture for a large software platform. Drive system design, platform capabilities (APIs, event-driven systems, data pipelines), cloud and DevOps practices, and AI/LLM integration. Solve cross-team technical problems, set engineering standards, mentor senior engineers, and align engineering with product and business strategy while ensuring reliability, security, and cost optimization.

Lead design and implementation of scalable media pipeline systems for consumer devices. Develop and optimize streaming solutions (DASH, HLS), integrate DRM (Widevine, PlayReady, FairPlay), extend media frameworks (GStreamer, FFmpeg), implement multi-threaded and IPC architectures, and ensure code quality through reviews and unit tests while collaborating with product, QA, and platform teams.

Design, build, and deploy ML models and end-to-end pipelines; implement MLOps practices; deploy containers to cloud production; monitor model performance and drift; collaborate with engineers and product teams; optimize latency and throughput; write production-quality code and mentor junior engineers.

Lead end-to-end client AI transformation engagements: discover business problems with executives, architect and build production-credible PoAs (data pipelines, RAG/LLM apps, integrations), deploy on client cloud, quantify ROI, present to stakeholders, and hand off to delivery teams while mentoring junior engineers and contributing reusable accelerators.

Monitor, detect, investigate, and respond to cyber threats across cloud, hybrid, and on-prem environments. Perform incident response, digital forensics, vulnerability management, threat hunting, and automate SOC workflows using SIEM, SOAR, EDR, and scripting (Python/PowerShell). Collaborate with cross-functional teams and contribute to detection engineering and playbook improvements.

Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.