Staff AI Engineer – Agentic AI and Automaton

About the Role:

We are looking for a seasoned Staff Engineer to lead the design and delivery of highly scalable, cloud-native backend, data, and AI systems with a strong focus on AI-driven automation and agentic workflows.

In this role, you will define the technical direction for the core TPA platform (Eligibility, Provider Data and others), enable intelligent, end-to-end workflows across systems, and drive the integration of AI into real-world business operations. You will operate at the intersection of backend architecture, data engineering, and applied AI, while mentoring engineers and influencing technical strategy across teams.

This is a hands-on leadership role for someone who thrives in ambiguous, high-impact problem spaces and can translate emerging AI capabilities into production-grade systems at scale.

What you'll do:

• Set the technical vision and drive architecture for scalable, cloud-native backend, data, and AI systems
• Design and build API-first and event-driven systems supporting internal and external integrations (partners, EDI, downstream platforms)
• Lead development of high-throughput data pipelines (batch + streaming) powering operational workflows and AI use cases
• Design and implement AI-driven automation and agentic workflows to reduce manual operations and enable intelligent decisioning
• Integrate LLM-based capabilities (search, summarization, copilots, workflow orchestration) into core platform services
• Establish best practices for AI systems (prompting, evaluation, guardrails, observability, responsible AI)
• Build and evolve integration layers across APIs, events, and file-based systems (including complex partner integrations)
• Improve data quality, validation, lineage, and real-time visibility across critical business workflows
• Drive adoption of AI-assisted development workflows (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate engineering velocity and delivery
• Partner with Product, Data, and Operations to translate complex workflows into scalable, intelligent systems
• Lead small but nimble teams, cross-team initiatives, influencing technical roadmap and AI adoption and implementation strategy
• Mentor sr. engineers and technical leads, raising the bar on system design, data engineering, and AI adoption

To be successful in this role, you'll need:

• 10+ years of experience building scalable, distributed backend systems and platforms
• Strong expertise in Java/Spring Boot and/or Python, with deep understanding of microservices architecture
• Proven experience designing and operating integration-heavy systems (APIs, event-driven systems, partner integrations)
• Hands-on experience with cloud-native architectures and Implementation (AWS and/or GCP)
• Strong experience building data pipelines and data-intensive systems (batch and/or streaming)
• Deep understanding of data engineering principles (data modeling, quality, lineage, observability)
• Experience working with complex data domains (e.g., transactional systems, EDI, or operational workflows)
• Hands-on experience integrating AI/ML or LLM-based capabilities into production systems
• Familiarity with RAG pipelines, embeddings, and vector-based retrieval systems
• Solid understanding of event-driven architectures (Kafka, queues, SQS) and distributed systems design
• Hands-on experience using AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate development
• Strong understanding of AI-augmented engineering workflows, including prompt-driven development, testing acceleration, and iterative refinement
• Proven ability to lead cross-team technical initiatives, influence architecture, and mentor senior engineers
• Strong communication skills with the ability to connect technical decisions to business impact

Our Tech Stack:

• Backend: Java / Spring Boot, Python
• Cloud: AWS, GCP
• Orchestration: Kubernetes,