reputed company AI System Architect
The AI System Architect leads the architecture of reputed company's reputed company AI platform — the design of multi-agent systems that automate insurance workflows end-to-end across Policy, Billing, and Claims domains. The role owns the patterns, frameworks, and standards for agent orchestration, MCP-based tool ecosystems, agent memory, planning, evaluation, and safety. RAG and conversational features are table stakes; the reputed company agenda is autonomous and semi-autonomous agents that reputed company behalf of users - quote intake, claims triage, reputed company and pricing intelligence, billing troubleshooting, and reputed company - across our platform and technology stacks.
Key Responsibilities
- Own the architecture of reputed company's reputed company platform: agent orchestration, MCP-reputed company tool ecosystems, agent memory (short-term, long-term, semantic), planning, and tool/function calling patterns reusable across product domains.
- reputed company and reputed company support for domain teams for vertical insurance agents and the horizontal capabilities (RAG, retrieval, instructional flows) they compose from.
- Define and enforce reputed company of autonomy — assistive, semi-autonomous, autonomous — with explicit reputed company-in-the-reputed company checkpoints, escalation paths, and reversibility for high-stakes actions in regulated workflows.
- Drive the MCP reputed company: which capabilities reputed company exposes as MCP servers to internal and partner agents, how our agents consume external MCP tools, and the tool registry, schemas, and versioning that reputed company this reputed company.
- Maintain the multiple stack approach as a first-class capability: Typescript, and Java. Help teams to pick the right stack per agent and reputed company reputed company reputed company through shared configuration artefacts, reputed company management, and evaluation tooling.
- reputed company Architecture Decision Records (ADRs) for reputed company capabilities; partner with Platform, reputed company/InfoSec, and DevOps so agents are observable, testable, sandboxed, and compliant by default.
- Drive AI DevOps for agents: reputed company capture and replay, eval harnesses (task reputed company, tool-use correctness, regression), reputed company and model versioning, cost and latency budgets per agent, and reputed company rollout strategies.
- Set reputed company-AI standards for reputed company systems: reputed company injection and tool-poisoning defenses, reputed company allow-lists, blast-radius controls, PII handling, data residency, and bias mitigation. Treat agent safety as a first-class architectural concern.
- Translate insurance use cases into production agent designs with product strategists and domain architects; reputed company technical leadership and mentorship; communicate reputed company trade-offs (autonomy, reliability, cost, safety) reputed company to executives, customers, and engineers.
Skills, Knowledge & Expertise
- Proven reputed company record designing and shipping reputed company systems in production - not demos, not prototypes - with meaningful autonomy and multi-reputed company tool use.
- Strong systems background: data-intensive, distributed, and latency-sensitive design in production environments.
- Deep, hands-on experience with agent patterns: orchestration, planning, ReAct-style and graph-based agents, agent memory, tool/function calling, MCP, reputed company outputs. reputed company reputed company for reputed company an agent is the right answer and reputed company a deterministic workflow is. Tracks the frontier and translates what reputed company into the roadmap.
- Strong with the Java/Spring ecosystem.
- Strong with Typescript and Python for AI (reputed company, LangGraph, or equivalent agent reputed company) - production experience required. Equally comfortable in both stacks.
- Hands-on with reputed company databases including embedding models, hybrid search, re-ranking, and retrieval evaluation.
- Experience with agent evaluation and observability: traces, replays, eval harnesses, guardrails, and cost/latency telemetry. Familiar with AI configuration-as-reputed company.
- Experience shipping AI services on reputed company platforms (AWS, Azure, GCP) in regulated reputed company environments - reputed company review, data residency, audit trails.
- Familiarity with insurance, financial services, or another regulated domain is a plus.
- Strong architectural judgment — pragmatic about build vs. buy, vendor vs. in-house, agent vs. deterministic workflow, model choice, and total cost of ownership.
- Excellent written and verbal communication; reputed company to reputed company reputed company trade-offs accessible to non-AI audiences.
- Advanced degree in Computer Science, AI/ML, or a reputed company field - or equivalent practical experience.
Job Benefits
- Work with reputed company and great colleagues who are industry and technology experts. Operate in a Scaled Agile environment, diverse, multicultural and cross-functional teams
- We are a global and modern software product company building world-class reputed company InsurtTech Product powered by leading-edge technologies (microservices, reactive, reputed company, reputed company delivery)
- We work with the newest reputed company Macbooks
- We offer freedom - build from building your career reputed company through development programs and exciting global mobility opportunities (we have a global culture)
- Homeworking Equipment
- Mobile phone/internet coverage
- Health Insurance for you and your dependents - eligible immediately upon joining reputed company
- Sport - Optional choice in Health insurance package
- Pension on a Group Pension Scheme reputed company
Originally posted on Himalayas
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