Associate Director - AI Platform Architect

Sirius AI is a US headquartered AI Consulting services and products company with operations in India. Sirius AI focuses on Financial Services enterprises and solutions / services delivered across multiple geographies.

We are an innovation-driven AI and data consulting firm with a strong focus on measurable business outcomes. Our team blends consulting, industry, and product engineering expertise across Data, Cloud, AI, Architecture, and Platform ecosystems.

Key Responsibilities:

1. Enterprise Architecture & Data Platforms

Engage with clients to understand their architecture, constraints and business objectives

Lead enterprise data platform builds from pre-sales shaping to production deployment

Define target architectures across channels, integration, cloud, data, microservices, and security

Modernize legacy ecosystems into scalable, AI-native platforms

2. Enterprise-Grade Agentic AI Platforms

Architect and build enterprise-grade Agentic AI systems leveraging LLMs, RAG, multi-agent

frameworks and tool-use architectures

Design and implement Agentic Operating Systems (Agent Orchestration Layers) enabling:

• Multi-agent collaboration
• Tool and API execution layers
• Short- and long-term memory management
• Guardrails and policy enforcement
• Human-in-the-loop workflows

Define reusable agent design patterns and enterprise agent SDK standards

Evaluate and productionize frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI,

etc.

3. Multi-Tenant Agentic AI Product Platform

Lead the architecture and development of a scalable, multi-tenant Agentic AI product platform

hosted on Sirius AI cloud infrastructure

Design the platform to support:

• Secure tenant isolation (data, memory, prompts, agents)
• Configurable client-level agent customization
• Role-based access controls (RBAC)
• Cost attribution & token usage metering per tenant
• Model routing & provider abstraction layers

Define and implement:

• Tenant onboarding workflows
• Secure data ingestion & RAG pipelines per client
• API gateway & SDK layers for enterprise integration
• White-label and configurable deployment models

Establish reusable core agent services that can be extended across multiple Financial Services

clients

Build a roadmap for evolving the platform into a repeatable AI product offering, not just bespoke

consulting delivery

Ensure platform scalability, resilience, and high availability across geographies

Define monetization-ready architecture (subscription, usage-based, hybrid models)

4. AI Governance, Observability & Reliability

Design and implement enterprise AI observability frameworks using:

• Langfuse
• Opik
• Weights & Biases
• Azure AI Studio monitoring
• Custom telemetry pipelines

Establish standards for:

• Prompt observability & version control
• Token and cost tracking
• Model & agent performance monitoring
• Agent traceability and execution logs
• Hallucination detection and evaluation pipelines

Implement offline + online evaluation loops for LLM and agent systems

Embed audit logging, compliance, explainability and AI risk controls suitable for Financial

Services enterprises

5. Cloud, DevOps & Platform Engineering

Lead Azure/AWS architecture including Compute, Storage, Networking, AKS/Kubernetes,

DevOps, Security and Monitoring

Implement MLOps / LLMOps pipelines for model lifecycle, prompt lifecycle and agent deployment

Drive performance tuning, resilience engineering, and cost optimization

Manage security findings, vulnerabilities and control gaps across applications and infrastructure

6. Strategic Advisory & Leadership

Act as trusted advisor to CTOs, CDOs and AI leaders

Drive GenAI and Agentic AI transformation roadmaps

Lead innovation programs, accelerators and reusable IP development

Build and mentor high-performance architecture and AI engineering teams

Shape Sirius AI's internal AI platform strategy and long-term product vision

Job Requirements

12+ years designing enterprise data and cloud-native platforms

5+ years as Principal / Lead Architect on Azure or AWS or GCP

Demonstrated experience building and productionizing GenAI or Agentic AI systems

Experience architecting multi-tenant SaaS or platform products

Hands-on exposure to:

• LLM architectures (OpenAI, Azure OpenAI, Anthropic, OSS models)
• RAG systems and vector databases
• Multi-agent orchestration frameworks
• Agent memory systems and tool-use design

Experience implementing AI observability and evaluation frameworks (Langfuse, Opik, etc.)

Strong understanding of:

• AI governance & risk controls
• Prompt lifecycle management
• Cost optimization for LLM workloads
• Subscription, self-hosted and hybrid deployment strategies

Expertise in CI/CD (Azure DevOps, GitHub Actions, etc.)

Experience in consulting services preferred

Experience building reusable AI accelerators and platform IP strongly preferred

Benefits

Work with a very innovative and collaborative firm focused on harnessing the power of AI and client's data for cutting edge solutions.

Founders are stalwarts of the AI and data consulting firms

Competitive salary and performance-based bonuses

Comprehensive health and wellness benefits

Work on cloud technologies and continue to invest in your professional growth

Collaborative and inclusive work environment