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

Dhaka Technologies Limited Company; Plano (TX); On-site; USD 51,000 - 73,000; Part time

Job summary

Dhaka Technologies Limited Company in Plano, TX is seeking an AI Engineer to design, build, evaluate, and operationalize the technical foundation of a Data Science & Machine Learning AI Accelerator. You will develop RAG pipelines, secure multi-agent workflows, and production-grade Python with governance and measurable impact.

The role emphasizes responsible AI, traceability, and collaboration with data scientists, ML engineers, and product teams in a contract setting.

Qualifications

• 5+ years in software, data science, ML, or AI engineering.
• Strong Python development skills with production-quality delivery.
• Experience building LLM-enabled applications and RAG systems.
• Knowledge of governance, privacy, and data-governance practices.
• Ability to translate ambiguous problems into testable technical requirements.

Responsibilities

• Design, build, evaluate, and operationalize the technical foundation of a DS/ML AI Accelerator.
• Develop retrieval-augmented generation pipelines and secure multi-agent workflows.
• Write production-quality Python and implement governance, traceability, and measurable impact.

Job description

Dhaka Technologies Limited Company | Contract

Plano, United States | Posted on 11/10/2026

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

About the Role

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.

Key Responsibilities

Governed Knowledge & RAG

• 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.

Agentic Product Engineering

• 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.

Evaluation, Delivery & Governance

• 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.

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 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 an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.