Top Tech Jobs & Startup Jobs in Austin, TX

Leads a span of approximately 20 engineers while shaping hiring, onboarding, career development, staffing, and engineering enablement across the AI practice. The role is also approximately 50% billable client delivery, providing executive advisory on AI software development lifecycles, governance, agentic deployments, MLOps and LLMOps pipelines, cloud platforms, observability, and production resilience. Requires extensive engineering leadership, organizational scaling, consulting, GCP, and production AI/ML deployment experience.

Lead organizational change and adoption for enterprise AI and cloud transformations. Develop change strategies, assess impacts, coach executives, manage resistance, activate change champions, design training and communications, facilitate workshops, measure adoption, and sustain new behaviors. Translate technical AI concepts into business value and guide Gemini Enterprise pilots using Google Workspace and related tools.

Own strategic enterprise accounts and drive multi-million-dollar growth by advising executives on data, AI/ML, and cloud transformation. Lead account strategy, solution design, scoping, pricing, negotiations, delivery orchestration, and alliance co-selling with Google Cloud and other partners. Build relationships with Fortune 500 and Fortune 1000 clients, exceed sales quotas, close new professional services business, and connect technical solutions to measurable business outcomes.

Leads the architecture, design, and implementation of scalable GCP and Databricks data lakehouse platforms. Designs real-time and batch pipelines, data models, governance, cataloging, security, and performance optimization. Advises clients, translates business requirements into technical solutions, leads project teams, mentors engineers, reviews architectures, and balances strategic planning with hands-on proof-of-concept and troubleshooting work.

Lead data engineering and machine learning initiatives by designing, architecting, developing, and supporting GCP data pipelines. Create information architecture documentation, estimate and plan technical work, collaborate with project teams and business analysts, and translate requirements into technical designs. Develop Python-based ELT pipelines, optimize BigQuery SQL, support CI/CD, and provide technical leadership to projects and teams.

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.

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.

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.