Senior AI Engineer

Paytm; Toronto; On-site; CAD 80,000 - 110,000; Full time

Job summary

Paytm in Toronto is seeking an experienced software engineer to build and deploy agentic AI systems across their workflows. You'll collaborate directly with teams and customers, ensuring safe and efficient use of AI in live transactions.

The ideal candidate has extensive experience in software engineering and AI systems, particularly LLM applications. Strong communication skills and experience with AWS/Azure are essential for this role.

Qualifications

• 5+ years in software engineering, with 3+ in AI systems or LLM applications.
• Strong grasp of LLM agent architectures and hands-on orchestration experience.
• Production experience on AWS and Azure with containerized deployments.

Responsibilities

• Embed & deploy agents in production environments.
• Own deployments end-to-end from discovery to activation.
• Lead technical direction and mentor engineers.

Skills

Software engineering

AI systems/LLM applications

Python proficiency

AWS and Azure experience

Agent architectures understanding

Stakeholder instincts

Agentic security understanding

Cloud AI/ML services

Tools

Docker

Kubernetes

Temporal

Airflow

Prefect

Job description

About the role

There’s a wide gap between an agent that works in a demo and one that works across millions of live transactions. Closing it is the job. You’ll embed with the teams and customers who depend on AI — risk, fraud, collections, payments, support, developer experience — and design, build, and ship agentic systems into their production environments. You’ll also help build the platform underneath: Paytm’s AI inference platform (Pi) and the agentic runtime, orchestration, and tooling that lets agents reason, plan, use tools, and run multi-step workflows safely.

Responsibilities

• Embed & deploy: Tackle greenfield problems alongside internal teams and customers — scope ambiguous needs and build agents from scratch that fit how they actually work.
• Own deployments end-to-end: discovery, build, integration, activation, and the tuning that earns trust and adoption.
• Lead pilots and demos, drive adoption, and clear blockers before they stall a rollout.
• Build agentic systems: Architect agentic systems — reasoning, planning, tool use, memory, multi-agent coordination — that run real workflows with guardrails.
• Build safe tool‑use infrastructure across APIs, databases, and services, with permissioning, sandboxing, and human‑in‑the‑loop.
• Ship SDKs, patterns, and reusable blueprints so internal teams build and deploy agents fast.
• Make it reliable: Design and run rigorous evals: measure quality, catch regressions, and feed results back into the system.
• Build observability, tracing, and guardrails that prove agents are safe and keep them safe as models and data drift.
• Own the multi‑model inference your agents depend on (text, voice, code, vision) — latency, throughput, and cost.
• Lead: Set technical direction and standards for agentic systems; mentor engineers and partner with ML, product, and security.

Qualifications

• 5+ years in software engineering, with 3+ in AI systems or LLM applications, and production systems shipped end-to-end.
• Strong grasp of LLM agent architectures (ReAct, RAG, tool use, multi‑agent) and hands‑on agentic orchestration and evaluation.
• Proficiency in Python across a broad stack — pipeline, agent, service, and instrumentation.
• Production experience on AWS and Azure with containerized deployments (Docker, Kubernetes).
• Strong customer and stakeholder instincts; able to impose structure on ambiguity and push back when needed.
• A bias toward shipping and comfort operating without a clean spec.
• Solid understanding of agentic security risks (prompt injection, privilege escalation, data leakage).
• Strong written and verbal communication.
• Experience with agentic systems in regulated industries (fintech, payments, credit, healthcare).
• Cloud AI/ML services (AWS SageMaker / Bedrock, Azure ML / Azure OpenAI); multi‑cloud or hybrid.
• MCP or agent communication standards; agent evaluation and observability tooling.
• Model serving (vLLM, TensorRT‑LLM, Triton), fine‑tuning, quantization, or LoRA.
• Workflow orchestration (Temporal, Airflow, Prefect) for AI workloads; voice / multimodal / edge inference.
• Testing and verification for non‑deterministic AI systems.

Why join?

Be among the first to define how agentic AI ships across a company running payments and credit at massive scale — with direct line of sight from your work to the outcome, and broad ownership across both the platform and the field.

Paytm Labs believes in diversity and equal opportunity and we will not tolerate any forms of discrimination or harassment. Our people are critical to our success and we know the more inclusive we are, the better our work will be.

Paytm Labs is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodations during the recruitment and selection process, please let us know.