Top Tech Jobs & Startup Jobs

Lead end-to-end deployments of autonomous LLM-powered agents in enterprise environments. Design RAG pipelines, multi-agent flows, and integrations; translate field feedback into scalable product features; architect production-grade AI solutions; act as technical consultant for clients, ensuring scalable, secure deployments.

Build and own end-to-end AI-powered product features for climate-tech clients: design UIs, implement scalable backends, integrate ML models, automate workflows, mentor junior developers, and collaborate with researchers and data engineers to deliver production-grade systems handling high-frequency environmental and industrial data.

Design and build an AI-native HR platform: backend systems (Python/Django/ASGI), integrate LLMs and agent frameworks, implement RAG/vector search, telephony/voice interfaces, and mentor junior developers while ensuring scalable, low-latency production deployments.

Build and maintain scalable backend services in Java or Kotlin using DDD. Modernize and refactor legacy systems, implement robust testing strategies, participate in mentoring code reviews, and work with messaging, databases, search, and AWS infrastructure to support a large cross-border marketplace.

Build, iterate, and maintain a production ML platform and pipelines. Support Data Scientists with tooling for deployment and monitoring, define MLOps roadmap and best practices, collaborate with Data Engineering and DevOps, and evaluate/integrate new ML frameworks and real-time inference tools.

Design, build, and deploy LLM-powered solutions and scalable backend systems. Implement data extraction, semantic search, document analysis, agentic flows, and evaluation frameworks. Continuously evaluate, tune, and improve model performance while collaborating with product, design, and legal teams.

Lead backend architecture and development for an AI-native HR platform using Python/Django and async frameworks. Integrate LLMs, RAG, vector DBs, telephony/voice, and agent frameworks. Collaborate with AI researchers, mentor engineers, design scalable systems, automate workflows, and deliver full-stack features with AI-assisted tools.

Design and run AI-enhanced sourcing campaigns, maintain structured talent pipelines in Google Workspace, conduct market research and competitor mapping, automate repetitive tasks, ensure accurate data and excellent candidate experience, and evolve sourcing strategies using free LLM and automation tools.

Lead full-stack development for a legal AI platform: design intuitive UIs and robust backends, integrate AI/LLMs with applications, architect scalable systems, mentor junior developers, collaborate with AI researchers, and automate systems for efficiency.

Lead end-to-end deployments of LLM-powered autonomous agents into enterprise workflows, build custom integrations and data pipelines, collaborate with R&D to convert field feedback into product features, architect production-ready AI solutions for large clients, and serve as a technical consultant for stakeholders.