Sirius AI
Website:
siriusai.com
Job details:
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
Click on Apply to know more.