Lead Engineer – Agentic AI & Java

Core AI Consulting Inc; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Core AI Consulting Inc. is seeking a Lead Engineer to drive the design and delivery of scalable enterprise backend applications using Java, Spring Boot, and microservices.

The role emphasizes agentic AI adoption across the SDLC, with focus on high-throughput architectures, event-driven design, and robust security. The ideal candidate brings 10+ years in software engineering, hands-on experience with Agentic SDLC, and proficiency in LangChain/LangGraph, Kafka, and Spring stack.

Qualifications

• 10+ years of software engineering experience, including 2+ years in a lead/principal role.
• Hands-on experience with Agentic SDLC to generate, review & test code.
• Experience building Agentic AI solutions using LangChain, LangGraph, AutoGen, CrewAI, Spring AI, or MCP-based tooling.
• Strong hands-on experience with RAG, prompt/context engineering, tool/function calling, structured outputs, agent evaluation, and observability.
• Proficiency in GenAI coding tools and AI-assisted engineering workflows in professional software development.
• Strong experience reviewing AI-generated code and designs for quality, security, performance, and maintainability.
• Expertise designing and operating high-throughput, scalable microservices and distributed systems.
• Familiarity with Kafka or similar event-streaming platforms and event-driven architecture.
• Deep Java (11/17/21) and Spring Boot, with Spring Cloud/Data/Security.
• Solid fundamentals in system design, data structures, databases, networking, cloud, and CI/CD.

Responsibilities

• Design and build AI agents and agentic workflows, including orchestration, tool/function calling, state and memory management, RAG, and human-in-the-loop controls.
• Integrate AI agents with enterprise applications, APIs, event streams, databases, and internal knowledge sources.
• Establish standards for prompt/context engineering, model selection, evaluation, guardrails, observability, security, and sensitive-data handling.
• Drive adoption of an AI-augmented SDLC across architecture, coding, testing, code review, documentation, and legacy modernization using tools such as Claude Code, GitHub Copilot, and Cursor.
• Apply spec-driven development, creating clear requirements, task decomposition, acceptance criteria, and reusable agent instructions/context.
• Evaluate AI-generated solutions for correctness, security, performance, maintainability, cost, and production readiness.
• Design and build high-throughput, low-latency Java/Spring Boot microservices, addressing concurrency, caching, connection management, horizontal scaling, and resilience.
• Build event-driven architectures using Kafka or similar platforms, including partitioning, consumer scaling, schema evolution, idempotency, retries, dead-letter handling, and replay.
• Design synchronous and asynchronous integrations using REST, gRPC, and messaging, including timeouts, retries, circuit breakers, and graceful degradation.
• Lead architecture and code reviews, mentor engineers, and define engineering standards for distributed systems and AI-assisted development.
• Own non-functional requirements including performance, scalability, availability, resilience, security, and cost efficiency.

Skills

Agentic SDLC

Java

System design

Mentoring

Code review

Education

Bachelor’s degree in Computer Science or related field

Tools

LangChain

LangGraph

AutoGen

CrewAI

Spring AI

MCP-based tooling

Kafka

Spring Boot

Spring Cloud

Spring Data

Spring Security

Claude Code

GitHub Copilot

Cursor

Job description

We are seeking a Lead Engineer with deep enterprise backend engineering experience and hands-on expertise in Agentic AI - SDLC. This role will lead the design and delivery of scalable, high-throughput applications using Java, Spring Boot, microservices, and event-driven architecture, while driving the adoption of AI agents and AI-augmented development practices across the SDLC.

Key Responsibilities

• Design and build AI agents and agentic workflows, including orchestration, tool/function calling, state and memory management, RAG, and human-in-the-loop controls.
• Integrate AI agents with enterprise applications, APIs, event streams, databases, and internal knowledge sources.
• Establish standards for prompt/context engineering, model selection, evaluation, guardrails, observability, security, and sensitive-data handling.
• Drive adoption of an AI-augmented SDLC across architecture, coding, testing, code review, documentation, and legacy modernization using tools such as Claude Code, GitHub Copilot, and Cursor.
• Apply spec-driven development, creating clear requirements, task decomposition, acceptance criteria, and reusable agent instructions/context.
• Evaluate AI-generated solutions for correctness, security, performance, maintainability, cost, and production readiness.
• Design and build high-throughput, low-latency Java/Spring Boot microservices, addressing concurrency, caching, connection management, horizontal scaling, and resilience.
• Build event-driven architectures using Kafka or similar platforms, including partitioning, consumer scaling, schema evolution, idempotency, retries, dead-letter handling, and replay.
• Design synchronous and asynchronous integrations using REST, gRPC, and messaging, including timeouts, retries, circuit breakers, and graceful degradation.
• Lead architecture and code reviews, mentor engineers, and define engineering standards for distributed systems and AI-assisted development.
• Own non-functional requirements including performance, scalability, availability, resilience, security, and cost efficiency.

Required Qualifications

• 10+ years of software engineering experience, including 2+ years in a Lead, Staff, Principal, or similar technical role.
• Proficiency and hands-on experience with Agentic SDLC to generate, review & test code.
• Proficiency and hands-on experience building Agentic AI solutions using technologies such as LangChain, LangGraph, AutoGen, CrewAI, Spring AI, or MCP-based tooling.
• Strong hands-on experience with RAG, prompt/context engineering, tool/function calling, structured outputs, agent evaluation, and observability.
• Proficiency in using GenAI coding tools and AI-assisted engineering workflows in professional software development.
• Strong hands-on experience to review AI-generated code and designs for quality, security, performance, and maintainability.
• Strong experience in designing and operating high-throughput, scalable microservices and distributed systems in production.
• Strong experience with Kafka or comparable event-streaming/messaging platforms and event-driven architecture.
• Deep hands-on expertise in Java 11/17/21 and Spring Boot, with experience in Spring Cloud, Spring Data, and Spring Security.
• Strong knowledge of REST/gRPC, Java concurrency, thread pools, caching, resilience patterns, and distributed-system design.
• Strong fundamentals in system design, data structures, databases, networking, concurrency, cloud, and CI/CD.
• Bachelor’s degree in Computer Science or related field, or equivalent practical experience.

Preferred Qualifications

• Experience with Spring WebFlux/Project Reactor or Java virtual threads.
• Experience establishing AI engineering standards or AI-enablement practices across development teams.
• Experience working in regulated industries such as financial services or healthcare.