As a Senior AI Developer, you will design and build the AI-powered tools and automation pipelines that our ES team relies on every day. You’ll work at the intersection of applied AI, enterprise software, and identity security — turning complex, knowledge-intensive processes into scalable, repeatable workflows. This is a hands-on building role with direct impact on how Saviynt serves its customers.
WHAT YOU WILL DOING
• Develop intelligent workflows that integrate large language models, search APIs, and data extraction tools to automate complex, knowledge-intensive processes.
• Implement quality-assurance mechanisms including confidence scoring, output validation, and human-in-the-loop review gates to ensure production-grade results from AI-generated outputs.
• Build and extend internal platforms and tools that enable Expert Services teams to deliver faster, more consistent outcomes at scale.
• Own critical automation pipelines end-to-end — from data ingestion and discovery through processing, validation, and packaged output delivery.
• Collaborate with domain experts, ES consultants, and product engineers to translate subject- matter expertise into automated, repeatable delivery patterns.
• Write clean, well-tested Python and Node.js code; build containerized services deployable on cloud infrastructure with industry-standard security practices.
• Contribute to internal tooling for ES delivery automation, operational efficiency, and project management integrations.
• Participate in architecture reviews, code reviews, and sprint ceremonies within a fast-moving, innovation-driven engineering team.
WHAT YOU BRING
• 2+ years hands-on experience building applications that integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, or similar).
• Proven experience with workflow orchestration platforms and multi-step automation pipelines.
• Strong understanding of REST API design, JSON/schema manipulation, and data extraction pipelines.
• Experience with Docker, Linux server administration, and cloud deployment (AWS preferred).
• Comfort working with semi-structured and noisy data; experience with validation loops and error-handling in AI-driven systems.
• Familiarity with Identity Governance & Administration (IGA), IAM, or enterprise SaaS integration patterns.
• Excellent written and verbal communication skills; ability to translate complex technical work into clear documentation
• Familiarity with agentic AI architectures, tool-use patterns, or multi-model orchestration in LLM applications.
• Experience building internal developer tools, CLI utilities, or self-service platforms.
• Background in Expert Services, consulting, or customer-facing delivery engineering.
• Exposure to prompt engineering best practices, structured output extraction, and retrieval-augmented generation (RAG) patterns.