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

Associate Director - AI Platform Architect