Lead AI engineer

We are seeking a Lead AI Software Engineer to own the technical direction and architecture of a next-generation, enterprise-grade agentic AI platform. Delivered as a single-tenant deployment into each customer’s cloud environment, the platform must scale across AWS, Azure, and GCP while operating securely behind enterprise identity providers and on sensitive financial data.

In this technical leadership role, you will guide the engineering team, set the overall platform architecture, lead complex distributed-systems engineering hands-on, and partner with Forward Deployment teams to ensure installation, execution, and isolation across diverse customer clouds.

Responsibilities

Engineering Leadership

• Lead and mentor a team of senior engineers.
• Establish technical standards, conduct thorough code reviews, and foster a culture of engineering excellence.

Platform Architecture

• Own the end-to-end architecture of the enterprise AI platform, including agent orchestration (LangGraph), tool execution, memory, retrieval (RAG), observability, identity, and authorization.
• Author Architecture Decision Records (ADRs) and make key decisions on data models, asynchronous patterns, caching, and deployment topologies.

Multi-Tenant & Cloud Foundations

• Design robust data isolation, identity, and access management for single-tenant customer-cloud installations, with a path to managed multi-tenant offerings.
• Architect integrations with multi-tenant SSO brokers (WorkOS) and policy decision engines (Cerbos).

LLM & Agent Safety

• Architect enterprise guardrails, prompt-injection defenses, PII redaction, and output-validation pipelines.
• Drive model routing, token budgeting, caching, cost discipline, and auditable, traceable agent decisions.

Hands-On Engineering & Delivery

• Lead challenging technical work involving distributed-systems edge cases, performance investigations under load, online migrations, and security architecture.
• Write high-quality Python code and partner with Product leadership to translate roadmaps into coherent, on-time engineering commitments.

Stakeholder & Client Alignment

• Act as the primary technical authority in customer discussions, CISO security reviews, and architecture deep-dives.
• Partner with Forward Deployment leads on deployment topologies.

Minimum Requirements

• 8+ years of commercial software engineering experience, including a proven record as a Tech Lead, Team Lead, or Principal Engineer leading complex distributed systems or AI projects.
• Experience shipping and operating LLM-based applications at scale, including expert prompt engineering, advanced RAG, tool-using agent frameworks (LangGraph), prompt-injection defense, evaluation pipelines, and cost/latency management.
• Deep expertise shipping multi-tenant products and understanding of shared-everything, shared-database, and isolated single-tenant/silo deployment trade-offs.
• Strong distributed-systems foundation, including idempotency, eventual consistency, queue-based asynchronous processing, and distributed locking.
• Strong security architecture knowledge, including end-to-end authentication and authorization, OWASP mitigation, and RBAC/ABAC.
• Advanced Python proficiency, working knowledge of TypeScript/Node.js, and strong PostgreSQL expertise under heavy load, including pool tuning, indexing, online migrations, and pgvector/vector stores.
• Strong AWS expertise and working knowledge of Azure or GCP, with focus on portable multi-cloud deployment topologies.
• Exceptional team leadership, mentoring, and written/verbal English communication skills for cross-functional and senior executive engagement.

Benefits

• Opportunity to work on bleeding-edge projects.
• Work with a highly motivated and dedicated team.
• Competitive salary.
• Flexible schedule.
• Benefits package, including medical insurance and sports.
• Corporate social events.
• Professional development opportunities.
• Well-equipped office.