Jobs at Egen

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.

Lead and scale North America talent acquisition as a player-coach: manage a team of three recruiters, run complex senior technical searches (engineering, AI, data, cloud), partner with executives, improve recruiting processes and tooling, and leverage AI/automation to boost recruiter productivity and hiring metrics.

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 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.

Lead architecture and hands-on implementation of large-scale Generative AI and agentic systems. Build production-ready RAG, embedding fine-tuning, vector search, and MLOps pipelines on Google Cloud. Advise clients in pre-sales, mentor engineers, and ensure reliability, latency, cost, and responsible-AI controls for high-stakes deployments.

Lead design and build of production Generative AI solutions (document intelligence, RAG, semantic search). Implement and optimize LLMs, embeddings, and agentic workflows, deploy on Google Cloud/Vertex AI, apply MLOps, monitor performance, and collaborate with clients to translate requirements into scalable, cost‑efficient AI systems.

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.