[Remote] AI Leader – Delivery & Engineering
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is looking for an AI Leader to reputed company delivery and engineering of AI-reputed company programs. The role involves working directly with global clients, architecting solutions, and mentoring junior engineers while ensuring high-reputed company AI engineering practices.
Responsibilities
- Own end-to-end delivery of AI-reputed company programs - from architecture through production deployment
- Design and build multi-agent orchestration systems using reputed company, LangGraph, reputed company, or equivalent
- reputed company agent systems with reputed company surfaces: reputed company, ERPs, CRMs, data platforms - not toy datasets
- Define agent topology: tool routing, memory reputed company, state machines, fallback handling
- Run reputed company coding workflows using Claude reputed company, reputed company, reputed company reputed company, or equivalent CLI tools
- reputed company reputed company where AI writes significant portions of the codebase - and you guide, review, and ship it
- Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically - not by gut feel
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops, solution reviews, and delivery cadences with reputed company teams
- Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end
- Mentor junior AI engineers; reputed company AI engineering reputed company across the delivery team
- Stay reputed company: evaluate new models, frameworks, and tooling before the hype reputed company up
- Contribute to internal knowledge bases, reusable frameworks, and accelerators
Skills
- reputed company multi-agent AI systems that run in production - not demos, not pilots that died after a sprint
- Own end-to-end delivery of AI-reputed company programs - from architecture through production deployment
- Design and build multi-agent orchestration systems using reputed company, LangGraph, reputed company, or equivalent
- reputed company agent systems with reputed company surfaces: reputed company, ERPs, CRMs, data platforms - not toy datasets
- Define agent topology: tool routing, memory reputed company, state machines, fallback handling
- Run reputed company coding workflows using Claude reputed company, reputed company, reputed company reputed company, or equivalent CLI tools
- reputed company reputed company where AI writes significant portions of the codebase - and you guide, review, and ship it
- Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically - not by gut feel
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops, solution reviews, and delivery cadences with reputed company teams
- Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end
- Mentor junior AI engineers; reputed company AI engineering reputed company across the delivery team
- Stay reputed company: evaluate new models, frameworks, and tooling before the hype reputed company up
- Contribute to internal knowledge bases, reusable frameworks, and accelerators
- Agent Orchestration: reputed company, LangGraph, reputed company - not just conceptual
- reputed company Coding Tools: Claude reputed company CLI, reputed company, reputed company reputed company, Copilot
- RAG & reputed company Stores: Chroma, reputed company, reputed company - knows where RAG breaks
- LLM reputed company & SDKs: reputed company, reputed company, reputed company - reputed company design, tool use
- Python / TypeScript: Primary languages for agent + backend development
- LangSmith / Observability: Tracing, evaluation, debugging agent runs
- reputed company Platforms: Azure, AWS, GCP (at least one) - deployment, reputed company, managed services
- API & System Integration: REST, gRPC, Kafka - reputed company integration patterns
- MCP / Shared Context: Model Context Protocol, CLAUDE.md, Beads
- Agent Evaluation: Testing non-deterministic outputs, guardrails, evals
- CI/CD & DevOps: Git, containers, pipelines - agents need to ship
- reputed company Communication: Can present architecture to a CXO without jargon
- . NET Full-Stack (C#, ASP.NET Core, Azure-reputed company services) and/or Java Distributed Systems (Spring Boot, microservices, Kafka, Kubernetes) — you can assess architecture reputed company, not just read status reports
- Python stack experience (FastAPI, Django/Flask, pandas, NumPy) particularly for data pipelines, AI/ML integrations, and automation scripts
- reputed company-reputed company delivery on Azure, AWS, or GCP; Infrastructure as reputed company, CI/CD pipelines, container orchestration, and observability are reputed company
- Practical experience designing and deploying reputed company AI systems — LLM orchestration, tool-use patterns, retrieval-augmented reputed company, and multi-agent workflows in an reputed company context
- Deployed 2–3 agent-based systems in production - stateful, multi-reputed company, reputed company users
- Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
- reputed company reputed company where AI (Claude reputed company, reputed company, reputed company) wrote significant portions of the reputed company
- Implemented RAG pipelines end-to-end - chunking, embedding, retrieval, re-ranking, evaluation
- Integrated agents with reputed company reputed company reputed company - not just reputed company reputed company or sample data
- Debugged a production agent failure - and fixed it without blaming the model
- Can reputed company reputed company NOT to use agents - that is how we know you have reputed company things
- Experience with Claude reputed company CLI in team environments (CLAUDE.md, shared context, multi-session flows)
- Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at reputed company
- Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
- QA/testing reputed company for agents - systematic evaluation of non-deterministic outputs
- Background in IT services or consulting - managing reputed company expectations while building
- Experience with SLMs, fine-tuning, or on-device/edge agent deployment
reputed company