Software Engineering Lead - AI-Augmented Software Development

Anthology Solutions Inc. is recruiting experienced Software Engineering Leads for an enterprise client’s engineering team. This Java-only role requires deep enterprise backend engineering experience and hands-on expertise in Agentic AI across the software development lifecycle (SDLC). You will lead the design and delivery of scalable, high-throughput applications using Java, Spring Boot, microservices, and event-driven architecture, while driving adoption of AI agents and AI-augmented development practices across the SDLC. Candidates must demonstrate competency in both Java and AI, with an AI mindset for software development. .NET-only profiles do not meet this requirement.

Engagement details

This position requires direct W-2 employment with Anthology Solutions Inc. Corp-to-corp (C2C), 1099, and employment through another staffing supplier are not available for this opening. Candidates based in Austin or the Dallas area, Texas, are preferred. The exact onsite/hybrid schedule and initial assignment duration will be confirmed during the hiring process. All applications and candidate submissions are handled by Anthology.

Responsibilities

Design and build AI agents and agentic workflows, including orchestration, tool/function calling, state and memory management, retrieval-augmented generation (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 specification-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.

10+ years of software engineering experience, including 2+ years in a Lead, Staff, Principal, or similar technical role.

Proficiency and hands-on experience with an agentic SDLC to generate, review, and 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 generative AI coding tools and AI-assisted engineering workflows in professional software development.

Strong hands-on experience reviewing AI-generated code and designs for quality, security, performance, and maintainability.

Strong experience modernizing legacy enterprise applications using AI-assisted development techniques.

Strong experience 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 a related field, or equivalent practical experience.

Preferred qualifications

Experience establishing AI engineering standards or AI-enablement practices across development teams.

Experience working in regulated industries such as financial services.