About the role:

Our client is looking for a seasoned AI Architect with deep expertise in cloud-native enterprise systems and Generative AI. You will define and deliver scalable, secure, production-grade GenAI architectures, including multi-agent, RAG, LLMOps and AgentOps systems, and lead cross-functional teams to build and run them.

Key Responsibilities:

- Architecture: Design modular, cloud-native GenAI systems (microservices, event-driven, serverless). Own system boundaries, data flows and integrations across LLMs, vector DBs, embeddings and tools. Produce architecture artifacts (C4, DFDs, sequence/ER diagrams, API contracts, trade-off decisions).

- GenAI & Agents: Build RAG pipelines, NL-to-SQL, fine-tuning and multi-modal solutions. Design multi-agent orchestration (planning, reasoning, secure tool use). Set standards for prompt engineering, memory models and context management.

- AI Security: Enforce agent identity, tool allowlists with human approval for high-risk actions, scoped tokens, sandboxed execution and auditable traces.

- Observability & Ops: Implement telemetry, tracing and logging. Monitor drift, hallucination and performance. Build dashboards, alerts and runbooks. Optimize cost (autoscaling, spot, serverless) and support FinOps.

- Leadership: Lead product, data science, AI and platform teams through architecture reviews and workshops. Maintain standards and pattern libraries. Mentor engineers.

Qualifications:

- 10+ years in software engineering, including 3+ years in architecture or senior technical leadership.

- Proven delivery of enterprise-scale, cloud-native production systems.

- Hands-on experience with LLMs, RAG, NL-SQL and agentic frameworks in production.

- Strong grounding in design patterns (microservices, event-driven, CQRS, hexagonal) and low-level design.

- Experience integrating ML/LLM services with enterprise data platforms under security and compliance requirements.

- Proficiency in two or more of Python, TypeScript, Go, Java, C#.

Tech Stack:

- Cloud & DevOps: AWS/Azure/GCP, Kubernetes, Docker, serverless, GPU instances, Terraform/Pulumi, CI/CD (GitHub Actions, Jenkins).

- GenAI & Agents: OpenAI APIs, LangChain, LlamaIndex, Semantic Kernel, Haystack, LangGraph, AutoGen, CrewAI.

- Vector Stores: FAISS, Pinecone, Weaviate, Chroma, pgVector.

- LLMOps/MLOps: MLflow, Kubeflow, TFX, BentoML.

- Data & Integration: Kafka, Spark, Airflow, Flink, API gateways (Apigee).

- Observability & Security: OpenTelemetry, Prometheus, Grafana, Datadog, ELK, Vault, OAuth2/OIDC/SAML, Snyk, SonarQube, OWASP.

- Backend/Frontend: FastAPI, Node.js, REST/gRPC/OpenAPI, React/Next.js, WebSockets/SSE.

Total Experience: 10-15 years