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Forward Deployment AI Engineer III (Embedded Solutions)
Insperity Services, L.P.
4 hours ago
Full-time
On-site
Houston, Texas, United States
The Forward Deployed AI Engineer III role at Insperity Services, L.P. is an embedded technical partner to business units, focused on building AI-powered solutions that improve operational effectiveness and help accelerate business outcomes. Working at the intersection of software engineering, data, and artificial intelligence, you will translate complex, real‑world challenges into scalable, production‑ready systems aligned with enterprise standards.
This is an onsite position in Kingwood, TX.
What you'll do
Partner with business stakeholders to understand workflows, identify inefficiencies, and uncover high‑value opportunities for AI‑driven solutions. Turn ambiguous business needs into practical AI approaches, including LLM‑based solutions, automation, and data‑driven techniques. Lead discovery sessions to align on problem definition, success criteria, and measurable outcomes. Design, build, and iterate on AI‑powered solutions with an emphasis on speed, usability, and business value. Create prototypes and proofs‑of‑concept using modern AI tools, including LLM APIs, agentic workflows, and orchestration frameworks. Refine solutions based on stakeholder feedback, usage patterns, and observed outcomes. Build end‑to‑end AI solutions tailored to business unit needs, including LLM applications, retrieval‑augmented generation (RAG) systems, and intelligent automation workflows. Use AI‑assisted development tools to accelerate design, coding, testing, and deployment activities. Apply architectural patterns that balance rapid delivery with long‑term scalability and maintainability. Move prototypes into production‑ready capabilities by improving performance, reliability, observability, and cost efficiency. Implement monitoring, evaluation, and feedback loops to measure solution effectiveness and business impact. Identify and mitigate risks including bias, hallucination, data leakage, and unintended AI behavior to support responsible AI practices. Align delivery with established enterprise architecture, security, and AI standards while maintaining speed and flexibility. Collaborate with centralized AI and architecture teams to leverage shared platforms, tools, and best practices. Share learnings, patterns, and knowledge back to the broader organization to improve repeatability and scaling. Serve as a trusted technical advisor and communicate complex technical concepts in clear, actionable terms for non‑technical audiences. Required qualifications
Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent demonstrated practical experience. Six or more years (6+) of experience in software engineering, data engineering, machine learning engineering, or AI system development. Experience delivering solutions in ambiguous, fast‑changing environments with a focus on business outcomes. Strong software engineering capability, including Python, APIs, and modern application development practices. Hands‑on experience designing and building AI/LLM‑based applications, including prompt engineering, RAG, and agentic workflows. Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Ability to rapidly prototype and iterate using modern AI development tools and platforms. Strong understanding of data modeling and data quality, and how data influences AI system performance. Practical knowledge of AI evaluation techniques and common failure modes such as bias, hallucination, and unintended behaviors. Ability to balance speed and scalability by making sound tradeoffs between rapid delivery and long‑term maintainability. Strong problem‑solving and analytical skills, especially translating business needs into technical solutions. Excellent communication and stakeholder engagement skills across technical and non‑technical audiences. Demonstrated adaptability, curiosity, and willingness to experiment with emerging AI tools and techniques. Technologies
Python, APIs LLMs, LLM APIs Agentic workflows Orchestration frameworks Retrieval‑augmented generation (RAG) Prompt engineering LangChain, LangGraph, LlamaIndex, Semantic Kernel Benefits
Generous paid time off Top‑tier medical, dental and vision benefits Health & wellness support Paid volunteer hours By aligning solution delivery with enterprise governance, architectural frameworks, and security standards, this role supports scalable adoption of AI across business units while contributing reusable patterns to the broader organization.
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Partner with business stakeholders to understand workflows, identify inefficiencies, and uncover high‑value opportunities for AI‑driven solutions. Turn ambiguous business needs into practical AI approaches, including LLM‑based solutions, automation, and data‑driven techniques. Lead discovery sessions to align on problem definition, success criteria, and measurable outcomes. Design, build, and iterate on AI‑powered solutions with an emphasis on speed, usability, and business value. Create prototypes and proofs‑of‑concept using modern AI tools, including LLM APIs, agentic workflows, and orchestration frameworks. Refine solutions based on stakeholder feedback, usage patterns, and observed outcomes. Build end‑to‑end AI solutions tailored to business unit needs, including LLM applications, retrieval‑augmented generation (RAG) systems, and intelligent automation workflows. Use AI‑assisted development tools to accelerate design, coding, testing, and deployment activities. Apply architectural patterns that balance rapid delivery with long‑term scalability and maintainability. Move prototypes into production‑ready capabilities by improving performance, reliability, observability, and cost efficiency. Implement monitoring, evaluation, and feedback loops to measure solution effectiveness and business impact. Identify and mitigate risks including bias, hallucination, data leakage, and unintended AI behavior to support responsible AI practices. Align delivery with established enterprise architecture, security, and AI standards while maintaining speed and flexibility. Collaborate with centralized AI and architecture teams to leverage shared platforms, tools, and best practices. Share learnings, patterns, and knowledge back to the broader organization to improve repeatability and scaling. Serve as a trusted technical advisor and communicate complex technical concepts in clear, actionable terms for non‑technical audiences. Required qualifications
Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent demonstrated practical experience. Six or more years (6+) of experience in software engineering, data engineering, machine learning engineering, or AI system development. Experience delivering solutions in ambiguous, fast‑changing environments with a focus on business outcomes. Strong software engineering capability, including Python, APIs, and modern application development practices. Hands‑on experience designing and building AI/LLM‑based applications, including prompt engineering, RAG, and agentic workflows. Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Ability to rapidly prototype and iterate using modern AI development tools and platforms. Strong understanding of data modeling and data quality, and how data influences AI system performance. Practical knowledge of AI evaluation techniques and common failure modes such as bias, hallucination, and unintended behaviors. Ability to balance speed and scalability by making sound tradeoffs between rapid delivery and long‑term maintainability. Strong problem‑solving and analytical skills, especially translating business needs into technical solutions. Excellent communication and stakeholder engagement skills across technical and non‑technical audiences. Demonstrated adaptability, curiosity, and willingness to experiment with emerging AI tools and techniques. Technologies
Python, APIs LLMs, LLM APIs Agentic workflows Orchestration frameworks Retrieval‑augmented generation (RAG) Prompt engineering LangChain, LangGraph, LlamaIndex, Semantic Kernel Benefits
Generous paid time off Top‑tier medical, dental and vision benefits Health & wellness support Paid volunteer hours By aligning solution delivery with enterprise governance, architectural frameworks, and security standards, this role supports scalable adoption of AI across business units while contributing reusable patterns to the broader organization.
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