Staff Software Engineer

Who you are

• Bachelor’s or Graduate degree in Computer Science, Software Engineering, or a related technical field
• 8+ years of professional software engineering experience developing backend systems, distributed architectures, or core platform tools
• 2+ years of experience operating explicitly at a Staff or Principal engineering scope
• Demonstrated technical leadership: Must have formal experience mentoring 2+ engineers, leading architecture review processes, or acting as the primary technical lead for a multi-engineer project team
• Strong hands-on coding skills in modern programming languages such as Java, Python, or Go
• Deep experience in microservices architecture, RESTful web services, and event-driven architectures
• AI Agents & LLM Orchestration: Hands-on experience building agentic workflows, multi-agent systems, and LLM integrations using LangGraph, AWS Bedrock, OpenAI API, and Anthropic API
• Infrastructure as Code (Terraform): Extensive, practical experience specifically using Terraform for cloud provisioning, state management, and scalable infrastructure deployment
• Domain Abstractions: Experience developing Domain-Specific Languages (DSL), Finite State Machines (FSM), and dynamic agent routing algorithms
• Data & State Infrastructure: Strong experience with Redis, Kafka, PostgreSQL, NoSQL databases, and streaming platforms
• Platform Infrastructure: Practical experience with containerization (Docker, Kubernetes) and cloud deployment on AWS
• System Resilience: Experience implementing reliability patterns such as Dead Letter Queues (DLQs), sidecar monitoring, automated secret management, and self-healing mechanisms
• Collaboration & Influence: Proven ability to mentor engineers, influence architectural choices, and partner across cross-functional product and security teams

What the job involves

• D.me is seeking a Staff Software Engineer (SDE V – Developer Experience & AI Platform) to lead the technical design, architecture, and execution of our internal developer platform and AI-driven automation infrastructure
• In this role, you will be responsible for building key developer tools, multi-agent workflows, and LLM orchestration systems that strictly target internal engineering workflows (e.g., service scaffolding, CI/CD automation, and developer-facing tooling) to empower engineering teams to build, deploy, and operate services efficiently at scale
• Please note: This role is focused entirely on internal developer experience. Experience building customer-facing conversational bots, chat products, or member-support automation does not substitute for internal platform and infrastructure engineering experience. This role is onsite 5 days a week in Mountain View, California
• This position sits at the intersection of platform engineering, developer experience, and artificial intelligence. You will lead hands-on development, establish architectural patterns, build stateful AI agent workflows, and set AI safety guardrails across the engineering organization. You will partner closely with SRE, security, and core infrastructure teams to create an integrated, high-velocity development ecosystem
• Architect AI-Augmented Developer Tools: Lead the hands-on building of internal developer platforms, service scaffolding, and automated CI/CD tooling that accelerate software delivery. This work explicitly targets internal engineering workflows, rather than customer-facing bots or member-support automation
• Design Agentic Systems & LLM Orchestration: Build multi-agent automation systems and adaptive conversational flows using frameworks such as LangGraph and foundation model APIs
• Develop Workflow Abstractions: Create Domain-Specific Languages (DSLs) and Finite State Machine (FSM) abstractions to model, control, and route complex multi-agent platform tasks
• Manage Stateful Context: Implement Near Real-Time Memory (NRTM) and shared session management to maintain persistent state and context across developer tools, bots, and internal APIs
• Build Resilient Distributed Systems: Implement high-availability orchestration patterns using Redis for state management, Kafka for event streaming, and custom Dead Letter Queue (DLQ) bridges for message reliability
• Establish AI Guardrails & Governance: Apply prompt engineering best practices, reduce model hallucinations, and enforce strict logging and safety standards so sensitive platform data is never exposed to external models
• Observability & Health Monitoring: Instrument microservices telemetry using sidecar patterns, data streams, and automated health checks to feed internal Datadog dashboards
• Technical Leadership & Mentorship: Coach mid-level and senior engineers, lead architectural design reviews, and establish engineering standards for AI agents and platform systems
• Measure & Optimize DevEx: Define and monitor key DevEx metrics (e.g., onboarding time, deployment success rates, task automation velocity) to continuously drive developer productivity

Benefits

• Company-Sponsored Medical, Dental, and Vision Plans for You and Your Family
• Paid Parental Leave
• Generous Paid Time Off
• 401K With Employer Matching
• Company-Sponsored Life Insurance
• Employee Equity Incentive Plan
• Remote Opportunities
• Multiple Lounge Areas and Game Room
• Numerous Mental Health Resources