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# Software Engineer (Hybrid)

- **Company:** Cisco Systems, Inc.
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $167,700.0 - $245,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Computing, Software Quality, Data Mapping, Data Structures, Relational Databases, Cursor, DevOps, Distributed Systems, Elasticsearch, Java Platform Enterprise Edition (J2EE), Spring Framework, Python (Programming Language), PostgreSQL, MongoDB, Object-Oriented Software Development, OpenShift, Oracle (Applications), Scaled Agile Framework, Software Engineering, TypeScript, GitHub Copilot, Evaluation Pipelines, Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, Technical Debt, Agentic-AI, Kubernetes, Machine Learning Operations, Claude, Api Design, Restful APIs, Cisco, Docker, Jenkins, Microservices, Oracledb
- **Published:** November 2, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88766151/1

## About the Role

* Bachelor's degree with 5+ years of software engineering experience in complex, large-scale enterprise environments, including proficiency in Java/J2EE, Spring, TypeScript, Python, Snowflake, and Oracle DB.
 * Experience designing, developing, and deploying full stack solutions, RESTful APIs, microservices, distributed applications, and leading projects from implementation to delivery.
 * Strong experience with cloud-based and relational databases (e.g., Elasticsearch, Vector DB, MongoDB, PostgreSQL, Oracle) and building solutions on AWS, Azure, and on-premises environments.
 * Expertise in Cloud and DevOps development using Docker, Kubernetes, OpenShift, Jenkins CI/CD.
 * Experience with AI-native engineering, including agentic frameworks, LLMs, RAG, multi-agent orchestration, and specialized AI tools (e.g., GitHub Copilot, Claude, Cursor).
 * Experience in M&A, digital transformation, or quote-to-cash integrations.

Preferred Qualifications

 * Knowledge of production monitoring, incident response, postmortems, and root cause analysis.
 * Deep architectural intuition with an API-first mindset.
 * Ability to thrive in high-velocity environments, navigating ambiguity to deliver innovative solutions.
 * In-depth conceptual and practical knowledge in primary technical job family and knowledge of related technical job families; has worked extensively with a range of technologies.
 * Strong background in object-oriented design, data structures, algorithms, testing, and software development principles.
 * Experience applying spec-driven development or similar approaches to improve software quality and delivery.

## Description

Mergers & Acquisitions IT team develops software platform to integrate acquired companies, accelerating operational synergy and time-to-value. We use secure coding practices, protect user privacy, and follow software development standards. We are looking for an experienced engineer who enjoys accelerating acquisition integration through automation, scalable software, and strong engineering practices! By joining this team, you will build relationships with a diverse set of global audiences and work with cutting-edge AI technologies to seamlessly integrate products, customers, bookings etc from acquired companies to Cisco.
Your Impact

You will lead the end-to-end technical integration of acquired entities, transforming disparate legacy stacks into cohesive, high-performance systems. You will champion an "AI-Native" engineering approach, using GenAI and agentic workflows to automate migrations and accelerate synergy realization while ensuring architectural integrity.

 * Design and develop modular, API-first solutions that bridge acquired entities with Cisco's enterprise stack, specifically targeting complex order-to-cash and subscription systems.
 * Deploy GenAI/LLM orchestration, RAG pipelines, and multi-agent systems to automate due diligence, data mapping, and migration testing.
 * Maintain technical standards (security, scalability, performance) across hybrid environments. Use design thinking to eliminate technical debt and ensure future-proof integrations.
 * Lead AI maturity assessments and implement LLMOps (observability, latency/cost optimization, and evaluation pipelines) to ensure production-grade reliability.
 * Improve the software development lifecycle and advance best practices in agile engineering.