Agentic AI Engineer

Shiv Software Experts LLC; Michigan; Remote; USD 180,000 - 250,000; Full time

Job summary

Shiv Software Experts LLC in Oakland, CA (Remote) seeks an experienced Agentic AI Engineer to design, build, and operationalize enterprise AI solutions grounded in trusted organizational knowledge.

This hands-on role covers discovery through deployment, monitoring, and continuous improvement, emphasizing business value, responsible AI, engineering quality, and measurable performance.

Qualifications

• Bachelor's degree in computer science or related field required; master's preferred.
• 10+ years in software/AI engineering with at least 2 years building and deploying large language model applications or agentic AI solutions.
• Proven experience designing, building, and operating production AI applications, preferably including AI agents, tool-using assistants, semantic search, or knowledge-grounded conversational apps.
• Hands-on experience with agentic AI or generative AI development frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or equivalents.
• Experience implementing AI application guardrails, access controls, monitoring, observability, and audit mechanisms.
• Strong understanding of responsible AI including privacy, security, explainability, transparency, human oversight, bias mitigation, and risk-based controls.
• Experience integrating AI applications with enterprise data platforms, content repositories, APIs, data services, and IAM capabilities.

Responsibilities

• Design, build, and deploy agentic AI solutions, including AI agents, multi-agent workflows, semantic search, grounded conversational assistants, and tool-using AI solutions.
• Develop reusable agent components, tools, connectors, orchestration patterns, evaluation assets, guardrails, and reference implementations that accelerate delivery of future enterprise AI solutions.
• Integrate AI solutions with enterprise knowledge graphs, ontologies, semantic models, APIs, data services, content repositories, and business systems to ground outputs and actions in trusted information.
• Select and integrate LLMs, agent frameworks, retrieval technologies, knowledge platforms, and vendor solutions; evaluate build-versus-buy based on requirements, enterprise architecture, security, cost, and complexity.
• Collaborate with enterprise architecture, cybersecurity, privacy, legal, compliance, and AI governance teams to ensure solutions conform to standards and obligations.
• Mentor engineers and contribute to broader agentic AI engineering capabilities, standards, reusable knowledge, and delivery practices.
• Support continuous improvement of the enterprise agentic AI delivery lifecycle from opportunity assessment to production deployment, monitoring, and retirement.
• Contribute to capability roadmaps, platform planning, reference architectures, and long-term enterprise solution delivery strategies.

Skills

Agentic AI

Responsible AI

Guardrails & Monitoring

Mentoring

Education

Bachelor's degree in CS or related

Master's degree preferred

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Job description

Role: Agentic AI Engineer

Location: Oakland, CA (Remote)

We are seeking an experienced agentic AI engineer to design, build, and operationalize enterprise AI solutions grounded in trusted organizational knowledge.

This is a hands on role for someone who is comfortable moving from use case discovery and solution design through implementation, testing, deployment, monitoring, and continuous improvement. The successful candidate will place equal emphasis on business value, user adoption, responsible AI, engineering quality, and measurable solution performance.

Key Responsibilities

• Design, build, and deploy agentic AI solutions, including AI agents, multi-agent workflows, semantic search, grounded conversational assistants, and tool-using AI solutions.
• Develop reusable agent components, tools, connectors, orchestration patterns, evaluation assets, guardrails, and reference implementations that accelerate the delivery of future enterprise AI solutions.
• Integrate AI solutions with enterprise knowledge graphs, ontologies, semantic models, APIs, data services, content repositories, and business systems to ground outputs and agent actions in trusted, governed enterprise information.
• Select and integrate large language models, agent frameworks, retrieval technologies, knowledge platforms, and vendor solutions, making sound build-versus-buy recommendations based on business requirements, enterprise architecture, security, cost, and operational complexity.
• Collaborate with enterprise architecture, cybersecurity, privacy, legal, compliance, and AI governance teams to ensure solutions conform to enterprise standards and regulatory obligations.
• Mentor engineers and contribute to the broader development of agentic AI engineering capabilities, standards, reusable knowledge, and delivery practices across the organization.
• Support continuous improvement of the enterprise agentic AI delivery lifecycle, from opportunity assessment and prototyping through production deployment, operational monitoring, and solution retirement.
• Contribute to agentic AI capability roadmaps, platform planning, reference architectures, and long-term enterprise solution delivery strategies.

Qualifications

• Bachelor s degree in computer science, software engineering, information systems, data science, or a related discipline is required. A master s degree in a related discipline is preferred.
• 10+ years of experience in software engineering, AI engineering, solution architecture, or related technical roles, including at least 2 years building and deploying large language model applications or agentic AI solutions.
• Proven experience designing, building, and operating production AI applications, preferably including AI agents, tool-using assistants, semantic search, or knowledge-grounded conversational applications.
• Hands-on experience with agentic AI or generative AI development frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or equivalent technologies.
• Experience implementing AI application guardrails, access controls, monitoring, observability, and audit mechanisms.
• Strong understanding of responsible AI principles, including privacy, security, explainability, transparency, human oversight, bias mitigation, and risk-based controls.
• Experience integrating AI applications with enterprise data platforms, content repositories, APIs, data services, and identity and access management capabilities.