Principal Agentic Architect

• We are seeking a Principal Agentic Architect to lead the design and delivery of enterprise-scale agentic AI systems across multi-cloud environments (AWS, Azure, GCP)
• This role requires deep hands-on expertise in LLMs, RAG, distributed systems, and cloud architecture, along with strong leadership in driving secure, scalable, and observable AI platforms

Key Responsibilities

• Platform Architecture (Multi-Cloud) Design and own the Agentic AI Platform (orchestration, RAG, guardrails, evaluation, observability) Define cloud architecture standards (VPC, IAM, networking, secrets, security) Implement secure communication (TLS/mTLS, WAF, service mesh)
• Agent Design Orchestration Lead development of complex agent workflows and multi-agent systems
• Define orchestration patterns, state machines, retries, fallbacks, and HITL flows
• Ensure reliable rollout strategies (canary, blue/green, feature flags) API Interoperability Standards Define REST APIs and SDK standards (Python/TypeScript)
• Ensure OpenTelemetry-based observability and traceability Standardize agent interoperability (MCP, A2A APIs) RAG Data Architecture
• Design RAG pipelines (embeddings, retrieval, chunking, prompt strategies) Integrate with enterprise systems (Snowflake, etc) Enforce schema-driven outputs and data contracts Security, Reliability Operations
• Drive SLIs/SLOs, monitoring, cost optimization, and performance tuning Implement PII protection, audit logging, and governance frameworks
• Lead incident response, RCA, and disaster recovery strategies Leadership Governance Lead architecture reviews and cross-team collaboration
• Provide technical mentorship and best practices Define architecture standards, ADRs, and governance processes Required Skills Strong expertise in Multi-Cloud Architecture (AWS / Azure / GCP) Deep experience with Agentic AI systems, LLMs, and orchestration frameworks
• Strong knowledge of RAG pipelines and vector databases (Pinecone, Weaviate, pgvector) Experience in microservices, APIs, and SDK development
• Expertise in observability (OpenTelemetry, Grafana, Prometheus)
• Hands-on experience with Docker, Kubernetes, CI/CD pipelines
• Strong understanding of security (IAM, encryption, mTLS, secrets management)
• Experience with evaluation frameworks and AI guardrails Strong programming skills in Python
• Good to Have Experience with LangGraph, AutoGen, CrewAI, LlamaIndex
• Knowledge of multimodal AI (document/image processing, OCR, extraction)
• Familiarity with policy-as-code, security compliance, and governance frameworks
• Experience in chaos engineering and DR strategies
• Exposure to advanced RAG (hybrid search, reranking, caching)
• Understanding of ML frameworks (PyTorch, Hugging Face)

Soft Skills

• Strong leadership and stakeholder management
• Excellent problem-solving and strategic thinking
• Ability to drive large-scale architecture decisions