Role Overview :

We are seeking an AI Integration Architect who specializes in the messy reality of system engineering. This role involves designing resilient, enterprise-grade ecosystems across AI, data, and cloud boundaries. You will own the entire lifecycle-transforming ambiguous, one-line business requests into concrete technical blueprints, building the foundational platforms, and ensuring production stability when things break. You are the ultimate technical authority the team turns to for complex, non-obvious integration challenges.

Key Responsibilities :

Architectural Translation & Alignment :

- Convert vague business goals into clear technical roadmaps.

- Align senior stakeholders and provide engineering teams with actionable, structured designs.

Robust Integration Design :

- Define API contracts, data flows, rate-limiting, and failure-handling strategies upfront.

- Own these architectures all the way through to production.

Developer Platform Ownership :

- Build and maintain secure, solid developer-facing API platforms, handling gateway configurations, quota management, and complex authentication (OAuth/Okta).

Production-Grade AI Orchestration :

- Connect AI components (LLMs, vector search, document pipelines) into production systems using Python/FastAPI, backed by strict contracts and operational runbooks.

Resilient Event-Driven Engineering :

- Design AWS-based asynchronous pipelines with built-in fault tolerance, including dead-letter queues (DLQs), smart retries, and distributed tracing.

Production Leadership & Governance :

- Lead incident triage, identify root causes, and establish high-quality reusable patterns and API standards that other teams naturally want to adopt.

Cross-Functional Guidance :

- Review infrastructure (Terraform/CI/CD) and frontend (React) code to guide delivery, ensuring alignment across the stack without needing to write frontend code yourself.

Technical & Professional Profile :

Experience & Leadership :

- 10+ years of engineering experience, featuring deep, proven ownership in technical leadership or architecture roles.

- A proven track record of thriving in ambiguity and maintaining high execution rigor.

- A culture of documentation-naturally writing clear API contracts, architecture decision records (ADRs), and runbooks.

Core Tech Stack :

- Backend : Expert-level Python and FastAPI.

- Cloud (AWS) : Deep expertise across Serverless (Lambda, Step Functions, EventBridge), Containers (EKS), Security/Networking (IAM, VPC), and Cost Optimization.

- DevOps & Infra : Hands-on experience delivering infrastructure via Terraform, Docker, and CI/CD pipelines.

- Security & Observability : Native implementation of Zero-Trust, SSO/OAuth, structured logging, and distributed tracing.

AI & Data Ecosystem :

- Note : Data Science/Model training expertise is not required.

- AI Architecture : Deep understanding of RAG, embedding pipelines, multi-agent workflows, and managing inference latency.

- Vector Databases : Practical knowledge of when and how to scale tools like Pinecone, FAISS, Weaviate, or Qdrant.

- Responsible AI : Ability to architect guardrails directly into data pipelines, including monitoring for bias, explainability, and safety.