Top Tech Jobs & Startup Jobs

Lead design, development, and productionalization of ML/GenAI applications including model evaluation, fine-tuning, prompt engineering, RAG pipelines, and scalable ML pipelines on cloud platforms. Mentor teams, collaborate on data preprocessing and feature engineering, and deliver reliable production ML systems involving vector search, inference serving, and monitoring.

Lead hands-on cloud implementation and technical ownership for Google Cloud environments: design, deploy, and operate secure, scalable infrastructure; implement hybrid connectivity, security guardrails, observability, and automation; lead delivery and mentor engineering teams.

Lead architecture and hands-on implementation of production-grade Generative AI and agentic systems. Build and deploy LLM-based solutions (RAG, embeddings, agents) on cloud (primarily GCP/Vertex AI), ensure reliability, latency, cost, observability, and governance, and advise clients while mentoring engineering teams.

Design and build full-stack applications that expose AI/ML insights. Develop backend services in Python, RESTful APIs, and containerized microservices. Build high-performance front-end interfaces with React/Vue/Angular. Implement cloud-native solutions on Google Cloud or Azure, manage relational and NoSQL databases, apply testing and CI/CD, and participate in Agile development and architecture sessions.

Drive revenue by designing tailored technical solutions, delivering product demos, writing proposals and RFP responses, validating integrations, managing stakeholder expectations, and supporting transition and delivery as a hands-on Forward Deployed Engineer (50% strategic delivery time). Serve as subject-matter expert in industry positioning and thought leadership.

Lead client-facing organizational change for AI and Workspace transformations: design change strategies, engage executives, build training and champion networks, run Gemini pilots, measure adoption, and sustain new behaviors across enterprises.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Lead enterprise cloud strategy and architecture on Google Cloud, drive multi-cloud interoperability, enforce governance and security, optimize cost, deliver large-scale implementations (GKE, BigQuery, Vertex AI), mentor senior engineers, and promote GitOps and automation across the delivery lifecycle.

The Client Partner will drive sales, maintain client relationships, oversee service projects, support marketing efforts, and manage account strategy within the East region.