Architect - Product and Platform Engineering

JD — AI Solution Architect (Fintech · Web, Mobile & Agentic)

Role

TheAI Solution Architect turns business goals intosecure, scalable AI/ML and agentic solutions:reference architecture,integration, andgovernance—withpayments-aware risk discipline.

Experience: 12–15 years in software/solution architecture; strong recent exposure toGenAI, agents, and production integrations.

Responsibilities

Area

Expectations

AI & agentic design

End-to-end solutions:LLM + tools (e.g. MCP-style),RAG/memory where grounding helps,guardrails,durable workflows (state, HITL, idempotency for multi-step flows).

Strategy & stack

Prioritize high-value use cases; definecloud/hybrid targets (AWS and/orAzure as applicable),model-agnostic patterns, cost/latency trade-offs.

Integration

APIs and events forweb, mobile, and agentic clients;goal-oriented machine-facing contracts alongside traditional channels; integration withCRM (e.g. Salesforce) and core platforms.

Security & access

AuthN/AuthZ for usersand automated actors (agents, services): least privilege, audit, secrets,no LLM→database direct access—tools/APIs only.

Operations

Observability forquality, latency, cost, abuse; evaluation and improvement loops (not one-off launches).

Compliance & ethics

Secure development, data minimization, alignment withfintech/regulatory expectations for AI use.

Evolution

Monolith → modular/API-first roadmaps (strangler, bounded contexts) includingagent-ready surfaces.

Technical profile

• AI/ML & agents: Practical depth with examples such asPyTorch / TensorFlow (classical ML),LangChain / LangGraph / LlamaIndex or equivalent (orchestration & RAG),MLflow or cloud ML ops where used.
• Cloud:AWS (primary ask) and/orAzure; identity, networking, observability.
• Data:Yes — required: pipelines (batch/stream), quality, andtimely data for models/agents—not optional at architect level.

Integration: REST/events, API gateways;Salesforce and enterprise systems intarget-state designs alongsideagents.