Become a Key Player as a VP of Engineering
You will lead and scale the engineering organization to deliver AI-powered products and a reusable technology platform that drives commercial adoption. You will partner with executive leadership, product, data, and customers to translate business and customer needs into technical roadmaps and production-ready capabilities. This is a hands-on leadership role where you will balance strategy and day-to-day engineering work.
Here's How You'll Make an Impact on the Team
- Own the engineering strategy, technical roadmap, architecture, and product delivery capabilities.
- Translate business priorities and customer requirements into clear engineering plans and executable initiatives.
- Lead products from discovery and POC through MVP, customer validation, production deployment, and scaling.
- Stay hands-on with architecture, code review, prototyping, debugging, and performance improvements.
- Design and develop APIs, backend services, data pipelines, AI workflows, and cloud infrastructure.
- Build and deploy generative AI, RAG, semantic search, AI-agent capabilities, and platform AI services.
- Establish engineering practices: code review, automated testing, CI/CD, release management, observability, incident response, and production support.
- Recruit, develop, and retain a high-performing engineering organization and define team structure, roles, and career paths.
- Implement security, compliance, and scalability practices for enterprise and regulated environments.
Here's What You'll Need to Be Successful in This Role
- Significant experience leading software engineering organizations (VP/Head/Director/founding engineer) in startup or growth-stage product companies.
- Proven track record taking software and AI products from concept to production and commercial adoption.
- Strong hands-on software engineering background; ability to engage in architecture, code, APIs, data systems, and infrastructure.
- Experience recruiting and scaling engineering teams and implementing development and operational best practices.
- Strong understanding of cloud architecture, distributed systems, data platforms, security, DevOps, and SaaS product development.
- Excellent communication skills and ability to work across engineering, product, commercial stakeholders, and executive leadership.
Here's What Else Might Help You Out
- Proficiency with Python and modern backend frameworks.
- Experience building REST APIs, microservices, data pipelines, event-driven systems, and distributed applications.
- Experience with generative AI, large language models, RAG, vector search, prompt engineering, and model evaluation.
- Familiarity with AWS services, PostgreSQL, Redis, OpenSearch, Snowflake, Databricks, vector databases, Docker, Kubernetes, Terraform, and CI/CD tools.