About the role
▶︎ Job Details ・Job Title: AI Engineer - DS&ML ・Client: Japanese Global Automotive Group / Cybersecurity & Enterprise Technology ・Working Location: Plano, TX (Hybrid – 4 Days Onsite) ・Employment Type : Contract (October 2026 – March 31, 2027) ・Visa Support: No ・Working Hours: Standard Business Hours (CST) ・Language: English Fluent
▶︎ Key Responsibilities * Design, build, evaluate, and operationalize enterprise-grade AI and Generative AI solutions supporting the DS/ML AI Accelerator. * Partner with data owners and business stakeholders to onboard approved documents, knowledge assets, and data sources into governed AI knowledge repositories. * Develop Retrieval-Augmented Generation (RAG) pipelines, metadata strategies, tagging frameworks, retrieval mechanisms, and source citation capabilities. * Create evaluation datasets and retrieval quality metrics to assess relevance, grounding, accuracy, and completeness of AI-generated outputs. * Ensure generated content clearly distinguishes factual information, assumptions, inferences, and areas requiring SME validation. * Design and implement secure multi-agent AI workflows leveraging LLMs, retrieval systems, APIs, and deterministic processes. * Define agent roles, workflow orchestration, tool integrations, validation rules, error handling, and human-in-the-loop review processes. * Develop reusable prompts, workflow patterns, and orchestration frameworks to improve scalability, governance, and user adoption. * Establish technical and business-oriented AI evaluation metrics, including correctness, traceability, latency, user effort, and operational cost. * Participate in Agile development processes, sprint planning, backlog refinement, and solution demonstrations. * Implement Responsible AI, security, privacy, data governance, and enterprise compliance requirements. * Create maintainable code, operational documentation, monitoring strategies, and knowledge refresh processes for long-term sustainability.
▶︎ The Right Candidate Will Possess * Strong hands-on experience developing and deploying LLM-enabled applications in production environments. * Deep understanding of RAG architectures, embeddings, vector databases, search technologies, and knowledge management. * Experience designing AI agent workflows and orchestrating tools, workflows, and APIs. * Strong software engineering background with modern development best practices and collaborative delivery models. * Ability to transform ambiguous business requirements into measurable and scalable AI solutions. * Strong analytical mindset with the ability to evaluate AI quality, reliability, and business value. * Excellent communication skills and ability to collaborate effectively with technical and non-technical stakeholders. * Commitment to responsible AI, governance, security, privacy, and compliance standards.
▶︎ Required Qualifications & Skills * Bachelor's degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent practical experience. * 5+ years of experience in Software Engineering, Machine Learning Engineering, Data Science, AI Engineering, or related technical disciplines. * Hands-on experience building LLM-powered applications, AI assistants, RAG solutions, or agentic AI systems. * Strong Python development experience with production-quality coding practices. * Experience with APIs, structured tool integrations, testing frameworks, code reviews, CI/CD, observability, and software documentation. * Knowledge of embeddings, vector databases, semantic search, retrieval systems, and AI evaluation methodologies. * Experience defining and measuring AI quality metrics, retrieval effectiveness, and user outcomes. * Ability to communicate technical concepts and tradeoffs to both business and technical stakeholders. * Experience working within security, privacy, governance, and Responsible AI frameworks. * Experience working in Agile development environments and delivering solutions in iterative sprint cycles.
▶︎ Preferred Qualifications * Experience with AI orchestration and agent frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar platforms. * Experience implementing LLM evaluation frameworks, guardrails, prompt management, telemetry, and model risk controls. * Experience supporting ML lifecycle management, model development, feature documentation, and AI product delivery. * Knowledge of enterprise data governance, auditability, access controls, and human-in-the-loop validation processes. * Experience working with Azure OpenAI, OpenAI, Anthropic, Gemini, AWS AI, or comparable enterprise AI platforms. * Experience deploying AI solutions within regulated or large enterprise environments.
No C2C: We do not accept Corp-to-Corp (C2C) arrangements for this position.