Lead Software Engineer- AI Agent Developer

JP Morgan Chase; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

JP Morgan Chase seeks a Lead Software Engineer (AI/ML) in Bengaluru to design and operate scalable autonomous agent systems for 100K+ customers. You will lead the architecture of agentic platforms, combining strong software engineering with hands‑on expertise in foundation models and LLM‑powered architectures.

Responsibilities include building instrumented, low‑latency systems, ensuring reliability, security, and observability, and mentoring engineers while advancing production AI standards and

Qualifications

• 8+ years of software engineering experience, with leadership in design and delivery of large‑scale systems.
• Hands‑on experience building and operating LLM/agentic systems in production with strict latency/reliability requirements.
• Strong knowledge of foundation models, prompting strategies, and tool‑augmented generation.

Responsibilities

• Architect and ship autonomous agent systems that are scalable, resilient, and production‑grade (latency, reliability, security, and uptime).
• Design agentic architectures (planner/executor patterns, multi‑agent orchestration, tool use, retrieval, and workflow execution).
• Build robust tool interfaces and tool ecosystems (APIs, function calling patterns, permissions, and safe execution).
• Engineer context, memory, and state management strategies (short/long‑term memory, summarization, retrieval, grounding, and caching).
• Own model evaluation and quality measurement (offline/online evals, regression testing, and failure‑mode analysis).
• Implement end‑to‑end observability for LLM systems (tracing, metrics, logging, prompt/tool telemetry, incident response).
• Drive cost and performance optimization across models and infrastructure (throughput, batching, caching, routing, quantization, and inference efficiency).
• Mentor engineers and set engineering standards for production AI systems (code quality, design reviews, and operational excellence).

Skills

LLM/agentic systems

8+ years software engineering

Leading design & delivery

Foundation models

Prompting strategies

API & distributed systems

Observability for AI

Python/Java/Go/TypeScript

Tools

Neo4J

OKFs

Vector databases

Job description

Join us to advance your software engineering career while building impactful technology solutions. Grow your skills and make a difference with a collaborative team.

We’re seeking a Lead Software Engineer (AI/ML) to build and operate scalable, low-latency autonomous agent systems in production. You’ll lead the design and delivery of agentic platforms that reliably serve 100K+ customers, combining strong software engineering fundamentals with deep hands‑on expertise in foundation models and LLM‑powered architectures.

Job responsibilities

• Architect and ship autonomous agent systems that are scalable, resilient, and production‑grade (latency, reliability, security, and uptime).
• Design agentic architectures (planner/executor patterns, multi‑agent orchestration, tool use, retrieval, and workflow execution).
• Build robust tool interfaces and tool ecosystems (APIs, function calling patterns, permissions, and safe execution).
• Engineer context, memory, and state management strategies (short/long‑term memory, summarization, retrieval, grounding, and caching).
• Own model evaluation and quality measurement (offline/online evals, regression testing, and failure‑mode analysis).
• Implement end‑to‑end observability for LLM systems (tracing, metrics, logging, prompt/tool telemetry, incident response).
• Drive cost and performance optimization across models and infrastructure (throughput, batching, caching, routing, quantization, and inference efficiency).
• Mentor engineers and set engineering standards for production AI systems (code quality, design reviews, and operational excellence).

Required qualifications, capabilities and skills

• 8+ years of software engineering experience, including leading design and delivery of large‑scale production systems.
• Demonstrated experience building and operating LLM/agentic systems in production with strict latency and reliability requirements.
• Strong understanding of foundation models, LLM behavior, prompting strategies, and tool‑augmented generation patterns.
• Strong understanding of Knowledge graph (Neo4J preferred), Open Knowledge formats (OKFs)
• Proven expertise in context and memory engineering, model evaluation methodologies, and quality measurement.
• Experience implementing observability for distributed systems and AI applications (tracing/metrics/logs, dashboards, alerting, on‑call readiness).
• Strong programming skills in one or more of: Python, Java, Go, or TypeScript; plus strong API and distributed‑systems fundamentals.
• Familiarity with retrieval systems, vector databases, and hybrid search patterns.

Preferred qualifications, capabilities and skills

• Agentic AI architecture: planner/executor patterns, multi‑agent orchestration, tool‑use design, retrieval workflows
• LLM/foundation model expertise: prompting strategies, tool‑augmented generation, model behavior understanding
• Context & memory engineering: short/long‑term memory, summarization, retrieval grounding, caching strategies
• Knowledge graphs: Neo4J (preferred), Open Knowledge Formats (OKFs)
• Retrieval systems: vector databases, hybrid search patterns