Lead AI Engineer

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world! **Job Description** Design, build, and scale enterprise-grade AI/GenAI solutions that automate business processes, enhance decision-making, and deliver measurable business outcomes. The role focuses on developing AI-powered applications, intelligent workflows, and integrations by combining enterprise systems, data, APIs, and modern AI technologies in a secure, scalable, and production-ready environment. **Responsibilities** * Design, develop, and deploy AI/GenAI applications, RAG pipelines, and intelligent workflow automation * Build backend services, APIs, integrations, and orchestration frameworks using LLMs, model APIs, and enterprise data. * Develop AI-powered knowledge assistants, workflow automation, and decision support solutions. * Leverage AI-assisted development while ensuring code quality, security, reliability, observability, and governance. * Define evaluation frameworks to measure AI quality, accuracy, latency, and system performance. * Collaborate with business, IT, Security, Data, HR, and Finance teams to identify and deliver high-value AI use cases. * Prototype rapidly and scale solutions into secure, production-ready deployments. * Optimize AI solutions for performance, scalability, reliability, and cost. * Develop reusable AI components, frameworks, and best practices to accelerate enterprise adoption. **Required Qualifications** * 7–12+ years of experience in Software Engineering, AI/ML, or GenAI application development. * Proven experience building and deploying production-grade AI/GenAI solutions. * Strong expertise in Python, backend development, APIs, system integration, and workflow orchestration. * Hands-on experience with RAG, LLMs, prompt engineering, tool/agent calling, AI evaluation, and observability. * Experience integrating enterprise applications, data platforms, and services using APIs and event-driven architectures. * Strong analytical, systems thinking, and problem-solving skills with the ability to translate ambiguous business problems into scalable AI solutions. **Preferred Qualifications** * Experience with vector databases, embeddings, semantic search, and advanced RAG architectures. * Knowledge of SQL, data engineering, and data pipelines. * Experience integrating AI into enterprise applications and business workflows. * Exposure to intelligent agents, automation platforms, and AI governance frameworks. * Experience building reusable AI frameworks, accelerators, or enterprise AI platforms.