Staff AI Platform Engineer - Inference & Agentic Systems

Paytm•Toronto, ON

48d

About The Position

We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience.

Requirements

8+ years of software engineering experience, with 3+ years in AI systems or LLM applications
Strong understanding of LLM-based agent architectures (ReAct, RAG, tool use, multi-agent systems)
Experience building highly reliable distributed systems
Proficiency in Python and experience working with modern LLM APIs or open-source models
Experience with or strong interest in model serving (vLLM, TensorRT-LLM, Triton)
Understanding of distributed systems: task queues, event-driven architectures, state management
Experience with cloud platforms (AWS, GCP) and containerized deployments
Strong understanding of security risks in agentic systems (prompt injection, privilege escalation, data leakage)
Demonstrated experience leading complex technical initiatives
Strong written and verbal communication skills

Nice To Haves

Experience building agentic systems in regulated industries (fintech, healthcare, enterprise)
Familiarity with Model Context Protocol (MCP) or agent communication standards
Experience with model fine-tuning, quantization, or LoRA
Experience building CI/CD automation and developer tooling
Experience adapting workflow orchestration systems (Temporal, Airflow, Prefect) for AI workloads
Experience with voice models, multimodal models, or edge inference
Experience designing human-in-the-loop or oversight systems
Interest in testing and verification for non-deterministic AI systems

Responsibilities

Build and operate multi-model serving across modalities (text, voice, code, vision) on shared infrastructure
Own the model lifecycle: download, deploy, serve, monitor, update, swap
Drive inference optimization: latency, throughput, cost - including quantization, batching, caching, and routing strategies
Ensure inference is fast and reliable for the agents and systems that depend on it
Architect and build the Agentic AI Platform - runtime infrastructure, orchestration systems, and developer tooling for autonomous agents
Design multi-agent coordination systems enabling agents to collaborate and solve complex workflows
Build robust tool-use infrastructure that allows agents to interact with APIs, databases, and services safely
Implement workflow automation: agents that execute multi-step business and engineering tasks with appropriate guardrails
Build safety and guardrail systems including permissioning, sandboxing, and human-in-the-loop workflows
Develop evaluation and observability frameworks to measure agent behaviour, detect regressions, and debug failures
Develop SDKs and APIs that allow internal teams to build and deploy agents quickly and safely
Define technical direction and architecture for agentic systems across the organization
Build patterns and standards for agent design, tool calling, and evaluation
Partner closely with ML, product, and security teams to deliver production-grade agent systems
Mentor engineers and contribute to best practices for agent system design