engineering lead ai agent solutions

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• Lead solution design across agent execution, memory, identity, tool integration, and observability
• Translate customer needs into clear requirements, compare alternatives, and explain the business and technical reasons for the chosen approach
• Guide the team's use of cloud-managed AI hosting services, including Bedrock, Azure AI Foundry, and Vertex AI
• Establish implementation patterns and validate platform choices against reliability, security, cost, and operational requirements
• Design and guide implementation of an LLM gateway and routing layer covering model tiering, quota and cost control, and observability
• Design and review memory, context, and state-management approaches for long-running workflows, including recovery, data retention, access boundaries, and isolation between users or engagements
• Set integration standards for MCP servers and tools used in authorized security workflows, including reconnaissance, scanners, controlled exploit tooling, and internal services
• Define permissions, approval requirements, auditability, and failure containment
• Establish a balanced testing and evaluation strategy covering software correctness, agent behavior, security boundaries, and operational performance
• Define release criteria and ensure the team can demonstrate they are met
• Guide production readiness and incident response, including observability, cost controls, staged delivery, rollback, and recovery
• Use operational evidence to prioritize improvements and technical debt
• Plan and prioritize technical delivery with product, security, and engineering stakeholders
• Break work into achievable milestones, delegate ownership, manage dependencies, and resolve technical and delivery impediments
• Build working prototypes and production-grade solution slices, taking them through implementation, testing, and deployment
• Lead complex troubleshooting and develop engineers through design reviews, coaching, and constructive feedback
• Improve engineering processes, contribute to technical hiring, and clearly communicate progress, risks, alternatives, and decisions to customers and the team

• Substantial experience delivering and operating production software, typically five or more years, including at least one year shipping LLM-based agents to production
• Demonstrated technical leadership and team delivery
• Strong programming skills and production depth in at least one general-purpose language, with practical agent development experience
• Ability to work across language boundaries, guide technology choices, and help the team adopt unfamiliar tools
• Ability to deliver working prototypes and production-grade implementations
• Experience designing system components or complete solutions, evaluating architectural alternatives, and making decisions based on business needs and non-functional requirements
• Deep experience with cloud-managed AI hosting services, including runtime, state, identity, integration, and observability concerns, and evidence of leading a team through adoption of an unfamiliar platform
• Practical expertise in MCP, tool orchestration, context and memory management, and agent evaluation, supported by a strong understanding of distributed-system failures and security boundaries
• Experience establishing or improving testing, CI/CD, observability, and engineering practices, and explaining how these practices improved quality, delivery, or operational outcomes
• Experience leading technical discussions with customers, presenting alternatives, and aligning stakeholders on scope, priorities, risks, and trade-offs
• Ability to plan team delivery, delegate effectively, resolve disagreements and impediments, mentor engineers, and conduct technical interviews
• Sound judgment when adopting AI development tools, with clear expectations for data access, permissions, review, and verification, and outcomes assessed through evidence
• English proficiency at B2 level or higher
• Будет плюсом: experience leading engineering work in application security, penetration testing, red-teaming, or security automation within an authorized scope; experience designing platforms for sandboxed code execution, browser agents, or autonomous tool orchestration; experience establishing reusable agent components, evaluation practices, or operational standards used by multiple teams; experience taking a new product or technical capability from initial design through launch and ongoing operation

• Условий в вакансии нет