Software Engineer with AI

Software Engineer with AI

Hybrid Sunnyvale, CA (2 days/week onsite)

6 months+

Only W2 Consultants

Needs:

• Software Engineering - front end or backend
• AI
• LLM
• RAG
• Agentic AI
• MCP
• Vector
• Python
• Cloud

Job Description:
Senior Software Engineer AI Systems

What you ll do

1. AI-Driven Software Development

• Build and deploy production-ready AI-powered services using LLMs and Generative AI.
• Develop and enhance components for RAG pipelines, agentic workflows, and knowledge-grounded reasoning systems.
• Write high-quality, testable, and maintainable code with strong focus on observability, reliability, and performance.

2. System Design & Scalable Engineering

• Design and implement scalable, cloud-native services and distributed systems for AI-powered applications.
• Own key service-level components across APIs, microservices, data pipelines, and vector-backed retrieval systems.
• Work with senior engineers and architects to improve system performance, latency, scalability, and fault tolerance.

3. Integration & Delivery

• Partner with product, platform, and data teams to integrate AI capabilities into business applications.
• Build robust APIs, backend services, and middleware to support adoption of AI solutions across use cases.
• Deliver features with a balance of speed, maintainability, security, and operational excellence.

4. Collaboration & Engineering Excellence

• Contribute to technical design discussions and help drive implementation for complex feature areas.
• Participate actively in code reviews, design reviews, and operational improvements to raise engineering quality.
• Mentor junior engineers and share best practices for building AI-enabled distributed systems.

What you ll bring

• 5+ years of experience in software engineering, with strong experience in backend systems, distributed systems, or cloud platforms.
• Hands-on experience working with Generative AI and LLM-based applications in applied or production settings.
• Strong coding skills in Python (preferred) and experience building production-grade backend systems.
• Experience building scalable microservices, APIs, and event-driven systems.
• Familiarity with vector databases, RAG pipelines, and LLM integration patterns.
• Exposure to AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face is a plus; focus is on application and system integration rather than model training.
• Good understanding of system design fundamentals and non-functional requirements such as performance, resiliency, and reliability.
• Track record of delivering production-quality software with strong ownership and cross-functional collaboration.