AI Engineer – DS&ML (GenAI / RAG / Agents) – Plano, TX – Req TTS173

## AI Engineer – Data Science & Machine Learning (GenAI / RAG / Agents)

**Req ID:** TTS173 **Location:** Plano, TX **Employment Type:** Contract – Corp-to-Corp (C2C) **Pay Rate:** $45 per hour (C2C) **Experience:** 5+ years in software, data science, ML, or AI engineering **Focus Areas:** Generative AI, RAG, Multi-Agent Workflows, LLM Evaluation, Responsible AI

### Minimum Qualifications

• Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
• 5+ years of software, data science, machine learning, or AI engineering experience, including production-quality Python development and collaborative version-controlled delivery.
• Hands-on experience building LLM-enabled applications, RAG systems, agentic workflows, or comparable AI assistants using APIs and structured tool integrations.
• Strong Python skills and modern software engineering practices: testing, code review, CI/CD, API design, documentation, and observability.
• Experience with data retrieval/indexing concepts, embeddings, vector or hybrid search, evaluation design, and quality measurement.
• Ability to turn ambiguous business problems into testable technical requirements and communicate tradeoffs to technical and non-technical partners.
• Demonstrated commitment to responsible AI, privacy, security, and data-governance practices.

### Preferred Qualifications

• Experience with modern LLM orchestration, agent-workflow, or developer-assistance platforms.
• Experience designing LLM evaluation frameworks, guardrails, prompt/version management, telemetry, or model-risk controls.
• Experience supporting ML lifecycle workflows, feature or data documentation, model development, or ML project bootstrapping.
• Familiarity with data governance, responsible AI, access control, auditability, and human-in-the-loop review.

### Key Skills

AI Engineer, Generative AI Engineer, GenAI, LLM Engineer, RAG, Retrieval-Augmented Generation, Agentic AI, Multi-Agent Systems, AI Agents, LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI API, Azure OpenAI, Embeddings, Vector Database, Hybrid Search, Knowledge Base, Prompt Engineering, LLM Evaluation, Guardrails, Responsible AI, MLOps, Python, CI/CD, API Design, Observability, Data Governance, Machine Learning, Data Science, Plano TX, Dallas

Dhaka Technologies is seeking an experienced AI Engineer to design, build, evaluate, and operationalize the technical foundation of a Data Science & Machine Learning (DS/ML) AI Accelerator in Plano, Texas.

You will do hands-on generative AI engineering: building retrieval-augmented generation (RAG) pipelines, designing secure multi-agent workflows, and writing production-quality Python, with a strong focus on governance, traceability, and measurable delivery impact.

• Partner with data and business owners to onboard approved documents, data definitions, prior work, and expert knowledge into a governed knowledge base.
• Implement retrieval pipelines, metadata, taxonomy, tagging, source citations, and quality checks that make context discoverable and trustworthy.
• Create evaluation datasets and retrieval-quality metrics; diagnose relevance, grounding, completeness, and source-stewardship gaps.
• Ensure generated outputs clearly distinguish retrieved facts, inferences, assumptions, and items that need subject-matter-expert confirmation.

• Design and build secure multi-agent workflows that retrieve approved context, coordinate LLM and deterministic steps, use tools safely, and produce structured, traceable outputs.
• Define explicit agent roles, tool contracts, workflow state, validation, error handling, stop conditions, and human review points for reliable multi-agent operation.
• Implement reusable prompt, workflow, and tool-orchestration patterns that improve repeatability, traceability, and usability for Data Scientists, ML Engineers, Business Analysts, Product Owners, and SMEs.

• Define and instrument technical and user-centered evaluation for agent outputs, including correctness, completeness, traceability, revision effort, latency, and cost-to-serve.
• Work in two-week agile sprints; demonstrate working increments, document technical decisions, and convert pilot feedback into a prioritized backlog.
• Apply secure development practices and meet Responsible AI, security, privacy, data-governance, and enterprise review-board requirements.
• Partner with the future operating owner to define maintainable code, runbooks, monitoring, knowledge-source refresh practices, and an enhancement backlog.

Submit your updated resume through the Dhaka Technologies Careers page. Please include your current location, availability, C2C employer details, and links or a short summary of LLM/RAG/agent systems you have built.