Software Engineer - AI Agents & Intelligent Systems

Experis
Oakland, United States of America
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Oakland, United States of America

Tech stack

API
Artificial Intelligence
Cloud Computing
Distributed Systems
Github
JSON
Python
Open Source Technology
Regression Testing
Reliability Engineering
Google Cloud Platform
Large Language Models
Multi-Agent Systems
Prompt Engineering
Backend
Data Strategy
AI Platforms
Optimization Algorithms
REST
Api Management
Microservices

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

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