Software Engineer - AI Agents & Intelligent Systems
Role details
Job location
Tech stack
Job description
We are seeking a highly skilled Software Engineer with deep expertise in AI-enabled application development, agentic systems, and modern cloud engineering to join our growing engineering organization in the Bay Area. This role is focused on building enterprise-grade intelligent systems powered by Large Language Models (LLMs), advanced Retrieval-Augmented Generation (RAG), and autonomous AI agents. The ideal candidate combines strong software engineering fundamentals with hands-on experience designing scalable AI architectures, deterministic agent workflows, and evaluation frameworks for production environments. You will work across engineering, product, platform, and AI research teams to design next-generation AI-enabled enterprise solutions at scale., AI Agent Engineering & Architecture
- Design and build enterprise-grade AI agents and agentic workflows using modern LLM frameworks
- Develop deterministic and controllable agent architectures for production reliability
- Implement agent skills, orchestration logic, memory strategies, and tool integrations
- Engineer prompt architectures and prompt optimization strategies for complex enterprise use cases
- Build scalable multi-agent systems with strong observability and governance controls, Software Engineering & APIs
- Develop scalable backend services using Python
- Build and integrate RESTful APIs and distributed service connections
- Work extensively with JSON-based data models and API contracts
- Contribute to open-source initiatives and maintain strong GitHub engineering practices
- Implement secure, scalable, and observable microservices architectures, * Build automated evaluation frameworks for LLM and agent performance
- Design testing and validation methodologies for AI agents
- Implement regression testing, benchmarking, hallucination detection, and output quality scoring
- Improve reliability, determinism, and operational safety of AI systems
- Establish CI/CD quality gates for AI-enabled applications, * Deploy and operate AI workloads on Google Cloud Platform (GCP)
- Work with enterprise cloud engineering and platform teams to operationalize AI solutions
- Optimize scalability, reliability, and cost efficiency across cloud-native systems
- Support platform integration initiatives including GECX and enterprise AI ecosystems
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 5+ years of software engineering experience
- Strong programming expertise in Python
- Experience building scalable APIs and distributed systems
- Strong understanding of JSON, API integrations, and backend architectures
- Hands-on experience with LLMs and generative AI application development
- Experience designing and building AI agents or agentic systems
- Experience with prompt engineering and context optimization techniques
- Experience building advanced RAG pipelines
- Familiarity with automated AI evaluation and testing frameworks
- Experience deploying solutions on GCP
- Strong GitHub and open-source development practices, * Experience with multi-agent orchestration frameworks
- Experience with vector databases and semantic search
- Familiarity with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar frameworks
- Experience implementing deterministic workflows and guardrails for AI systems
- Exposure to enterprise compliance, governance, and responsible AI practices
- Experience with observability, telemetry, and AI system monitoring
- Experience operating large-scale enterprise AI platforms, * Python
- APIs & Service Integration
- JSON
- GitHub & Open Source Development
- Distributed Systems
AI & Agent Architecture
- Agentic Coding & Agent Building
- Prompt Engineering
- Deterministic Agent Design
- Agent Skills & Tooling
- Multi-Agent Systems
LLM & Data Strategy
- Large Language Models (LLMs)
- Advanced RAG
- Context Optimization
- Progressive Disclosure
- Knowledge Retrieval Architectures
Testing & Evaluation
- Automated Evaluation Frameworks
- Agent Testing & Validation
- AI Reliability Engineering
- Benchmarking & Regression Testing