AI Engineer - DS&ML - Cinter Career

• 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.

• 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.

• 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.

• 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.