More jobs:
Job Description & How to Apply Below
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 Serving
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
Agentic Systems
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
Platform & Technical Leadership
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
What You'll Bring
8+ years of software engineering experience, with 3+ years in AI systems or LLM applications
Strong understanding of LLM-based agent architectures: tool use, multi-step workflows, multi-agent coordination, and their failure modes
Experience building highly reliable distributed systems
Experience evaluating LLM systems in production: building evals, detecting regressions, and debugging non-deterministic failures
Proficiency in Type Script or Python, and willingness to work in both: the agent platform is Type Script 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 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 Have
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
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
Search for further Jobs Here:
×