About the role
Advanced AI Full Stack Engineer responsible for designing and building foundational systems for autonomous AI agent platforms. The role focuses on engineering orchestration runtimes, sandboxed execution environments, and inference routing layers using Python, Node.js, and distributed systems architecture.
ConsultingOnsiteOther Functions
Key Responsibilities
- Design and build agent orchestration runtimes as stateful execution loops coordinating tool discovery, model inference, and context management
- Implement sandboxed execution environments with declarative policy enforcement for network egress, filesystem, and compute quotas
- Develop pluggable provider interfaces to ensure sandbox backends like container-based or microVM-based environments are swappable
- Build Python and Node.js/TypeScript SDKs and CLIs that provide interfaces for authoring and validating AI agents
- Design REST, gRPC, and event-streaming APIs to serve as the communication backbone between agent runtimes and platform services
- Engineer multi-tier memory architectures spanning in-process memory, cross-session relational stores, and vector databases
- Implement ephemeral credential injection and RBAC-scoped data access for least-privilege agent operations
- Instrument platform components with distributed tracing (OpenTelemetry) and latency metrics for observability
- Build CI/CD governance tooling to enforce schema correctness and regulatory constraints before agent package promotion
- Provide technical guidance on platform architecture decisions and engineering best practices to cross-functional teams
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related field (or equivalent work experience)
- 2 years of experience with Python and/or Node.js/TypeScript building production backend services or platform tooling
- 1 year of experience building or integrating with AI/LLM systems, agent frameworks, or AI developer tooling
- Strong track record of building and shipping developer-facing platforms, SDKs, or APIs (Preferred)
- Experience in agent orchestration frameworks, inference serving infrastructure, or sandboxed execution environments (Preferred)
- Hands-on experience with async Python frameworks such as FastAPI and asyncio
- Proficiency with containerisation and Kubernetes
- Experience with event-streaming protocols including WebSocket, SSE, and gRPC
- Technical knowledge of vector and relational databases
- Familiarity with AI agent protocols such as MCP, ACP, and A2A
- Familiarity with modern AI framework ecosystems including LangGraph, OpenAI Agents SDK, and Anthropic Claude SDK
- Ability to travel from 0 to 100% depending on business need and client requirements