Principal AI Engineer

4 months ago

Hyderābād, IndiaStaff+

Responsibilities

Own the architecture of a shared AI platform covering multi-agent orchestration, ML inference, LLM gateways, tool registries, and evaluation and observability.
Define architecture decision records, reference architectures, integration patterns, and build-versus-buy decisions.
Set AI product strategy in partnership with Product and the CTO office, including capability evaluation, cost analysis, and competitive positioning.
Establish AI FinOps practices for token metering, model routing, quotas, and budget forecasting.
Define responsible AI, content safety, PII governance, bias testing, model validation, transparency, explainability, fairness, and audit processes.
Ensure AI systems meet PCI DSS, SOC 2, financial regulations, and internal compliance standards.
Write production code, review critical pull requests, debug agent interactions, prototype capabilities, and build MCP integrations and automation workflows.
Mentor engineers, lead design reviews, define engineering standards, and train teams on Claude Code and agentic development workflows.

10+ years of software engineering experience and 5+ years of AI/ML experience architecting and shipping production AI systems.
Mastery of system design involving multi-agent architectures, ML platforms, or large-scale inference systems.
Deep expertise with Azure and the Microsoft AI stack, including Azure ML, AI Foundry, Semantic Kernel, and .NET agent frameworks.
Bilingual Python and .NET/C# development experience, using Python for ML/data workloads and .NET/C# for agent runtimes.
Experience with production-scale LLM systems, prompt management, retrieval-augmented generation, content safety, and agentic workflows.
Experience using Claude Code, Cursor, or an equivalent AI-first development accelerator.
Deep experience architecting modern .NET cloud-native platforms, including API-first services, distributed systems, Kubernetes deployments, gateway integration, and CI/CD governance.
Bachelor’s degree in Computer Science, AI/ML, Mathematics, or a related technical field.
Preferred experience includes fintech or payments architecture, PCI DSS, SOC 2, regulated AI, Google A2A, MCP, Visa TAP, technical leadership, omnichannel or voice AI, ML platform engineering, and published or open-source AI/ML contributions.

501-1,000 employees