About the Role
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.
What You'll Do
Inference & Model ServingBuild and operate multi-model serving across modalities (text, voice, code, vision) on shared infrastructureOwn the model lifecycle: download, deploy, serve, monitor, update, swapDrive inference optimization: latency, throughput, cost - including quantization, batching, caching, and routing strategiesEnsure inference is fast and reliable for the agents and systems that depend on it
Agentic SystemsArchitect and build the Agentic AI Platform - runtime infrastructure, orchestration systems, and developer tooling for autonomous agentsDesign multi-agent coordination systems enabling agents to collaborate and solve complex workflowsBuild robust tool-use infrastructure that allows agents to interact with APIs, databases, and services safelyImplement workflow automation: agents that execute multi-step business and engineering tasks with appropriate guardrailsBuild safety and guardrail systems including permissioning, sandboxing, and human-in-the-loop workflowsDevelop evaluation and observability frameworks to measure agent behaviour, detect regressions, and debug failuresDevelop SDKs and APIs that allow internal teams to build and deploy agents quickly and safely
Platform & Technical LeadershipDefine technical direction and architecture for agentic systems across the organizationBuild patterns and standards for agent design, tool calling, and evaluationPartner closely with ML, product, and security teams to deliver production-grade agent systemsMentor engineers and contribute to best practices for agent system design What You'll Bring
8+ years of software engineering experience, with 3+ years in AI systems or LLM applicationsStrong understanding of LLM-based agent architectures: tool use, multi-step workflows, multi-agent coordination, and their failure modesExperience building highly reliable distributed systemsExperience evaluating LLM systems in production: building evals, detecting regressions, and debugging non-deterministic failuresProficiency in TypeScript or Python, and willingness to work in both: the agent platform is TypeScript on Bun with Temporal workflows on Kubernetes and EC2, the inference platform is Python. 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, and durable long-running workflows Experience with cloud platforms (AWS, GCP) and containerized deploymentsStrong understanding of security risks in agentic systems (prompt injection, privilege escalation, data leakage) Demonstrated experience leading complex technical initiativesStrong written and verbal communication skills Nice to Have
Experience building agentic systems in regulated industries (fintech, healthcare, enterprise) Familiarity with Model Context Protocol (MCP) or agent communication standardsExperience 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
Go Big or Go Home!
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.
We thank all applicants, however, only those selected for an interview will be contacted.
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.
