Software Engineer | AI & Automation

Trace3•Irvine, CA

6h•$121,000 - $140,000•Hybrid

About The Position

The Software Engineer | AI & Automation is responsible for designing, building, integrating, and deploying software solutions that use artificial intelligence to automate business processes and improve how employees work across the organization. This is a software engineering role with a specialization in AI, focused on building production applications, APIs, enterprise integrations, AI agents, copilots, and intelligent workflows. The role will initially support AI initiatives across executive leadership, Sales, Operations, Legal, IT, and other business functions. The ideal candidate is a strong software engineer with hands-on experience using modern large language models (LLMs) and AI technologies to solve real business problems. This role works across the full engineering lifecycle—from translating business requirements into technical solutions through development, deployment, monitoring, and continuous improvement. Trace3 primarily operates within the Microsoft Azure ecosystem.

Requirements

Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field, or equivalent professional experience.
Minimum 4 years of professional software engineering or application development experience.
Strong programming skills, with Python preferred.
Experience building APIs, backend services, integrations, or business applications.
Experience integrating applications with databases, SaaS platforms, APIs, or enterprise systems.
Understanding of modern software engineering practices including testing, source control, logging, error handling, authentication, and application security.
Experience building and deploying applications within a major cloud platform; Microsoft Azure preferred.
Hands-on experience developing applications using large language models or generative AI technologies.
Understanding of LLM concepts including prompting, RAG, structured outputs, embeddings, semantic retrieval, and tool/function calling.
Experience or demonstrated knowledge building AI agents, copilots, intelligent workflows, or AI-enabled automation.
Strong debugging, analytical, and problem-solving skills.
Ability to translate evolving or ambiguous business requirements into practical technical solutions.
Ability to work independently while collaborating effectively with technical and business teams.
Ability to communicate technical concepts clearly to both technical and nontechnical audiences.

Nice To Haves

Azure OpenAI or Azure AI services.
Agentic AI and multi-step tool-calling workflows.
Model Context Protocol (MCP) or similar AI integration standards.
Containers, serverless applications, and CI/CD practices.
Open-source LLMs or multi-model architectures.
Experience moving AI prototypes or proofs of concept into production applications.
OpenAI, Anthropic, or other commercial LLM APIs.
Semantic Kernel, LangGraph, LangChain, or similar AI orchestration frameworks.
Microsoft 365 or Microsoft Graph integrations.
ServiceNow, NetSuite, or similar enterprise platforms.
Vector databases and enterprise search technologies.
AI application evaluation and observability.

Responsibilities

Design, develop, test, and maintain production software applications and services.
Build backend services, APIs, integrations, and reusable application components, primarily using Python.
Translate business requirements into practical and scalable technical solutions.
Develop reliable software using sound engineering practices including testing, source control, logging, error handling, authentication, and security.
Build reusable components and patterns that can support multiple applications and automation use cases.
Design and build AI-powered applications, agents, copilots, and intelligent workflows.
Integrate large language models into applications using cloud-hosted, commercial, or open-source models.
Build workflows that allow AI applications to retrieve information, call tools and APIs, and perform controlled business actions.
Develop solutions using concepts such as RAG, prompting, structured outputs, embeddings, semantic search, and tool/function calling.
Evaluate and improve AI application accuracy, reliability, performance, and cost.
Implement appropriate validation, guardrails, fallback behavior, and human oversight where needed.
Integrate applications with enterprise platforms such as Microsoft 365, ServiceNow, NetSuite, databases, internal systems, and third-party SaaS platforms.
Develop APIs, connectors, webhooks, and automated workflows.
Work with structured and unstructured data to support applications and AI solutions.
Identify opportunities where software, automation, and AI can reduce manual business processes.
Design integrations and services that can be reused across multiple business functions.
Build and deploy applications primarily within Microsoft Azure.
Participate in application deployment, CI/CD, testing, monitoring, and release processes.
Monitor and troubleshoot production applications and integrations.
Build solutions with appropriate consideration for scalability, reliability, security, and cost.
Ensure applications and AI solutions align with Trace3 security, privacy, governance, and data protection standards.
Implement appropriate controls around access to enterprise data and actions performed by AI-enabled applications.
Partner with AI leadership to evaluate risks, guardrails, and new AI capabilities before deployment.
Partner with AI leadership and business stakeholders to translate business problems into technical solutions.
Prototype and evaluate new ideas while helping successful concepts move into production.
Communicate technical concepts and tradeoffs to both technical and nontechnical stakeholders.
Contribute to shared engineering standards, reusable components, and development best practices.
Evaluate emerging AI technologies based on their practical value to the organization.