AI Engineer - DS&ML

OP; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

401(k)

Dental Insurance

Health insurance

Vision insurance

Job summary

OP is seeking an experienced AI Engineer to design and operationalize the AI foundation for the DS/ML AI Accelerator. You will own hands-on generative AI engineering, RAG pipelines, and agent workflows with a strong focus on governance, traceability, and measurable impact.

You will collaborate with data owners and business stakeholders, implement secure multi-agent patterns, and drive two-week sprints with clear documentation and backlogs to deliver reliable AI capabilities at scale.

Responsibilities

• Governed Knowledge and RAG: onboard documents, data definitions, and expert knowledge into governed KB.
• Implement retrieval pipelines, metadata, tagging, citations, and quality checks for trustworthiness.
• Create evaluation datasets and retrieval-quality metrics; diagnose gaps in relevance, grounding, and source stewardship.
• Ensure generated outputs clearly distinguish retrieved facts, inferences, assumptions, and SME-required items.
• Agentic Product Engineering: design secure multi-agent workflows that retrieve context, coordinate steps, and produce traceable outputs.
• Define agent roles, tool contracts, workflow state, validation, error handling, and human review points.
• Implement reusable prompt, workflow, and tool orchestration patterns for repeatability and transparency.
• Evaluation, Delivery, and Governance: define instrumentation for evaluation, document decisions, and convert feedback into backlog.
• Work in two-week sprints; maintain code quality, security, and governance; ensure enterprise reviews and monitoring.

Skills

Python

LLM-enabled applications

RAG systems

Agentic workflows

APIs and tool integrations

Education

Bachelor's degree in Computer Science, Data Science, Machine Learning, or related field

Job description

We are seeking an experienced AI Engineer to design, build, evaluate, and operationalize the technical foundation of the DS/ML AI Accelerator. The successful candidate will be responsible for hands-on generative AI engineering, retrieval-augmented generation (RAG), agent workflow design, and software engineering with a strong focus on governance, traceability, and measurable delivery impact.

Essential Functions

• Governed Knowledge and 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, and 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 Qualification

• 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 experience with 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 nontechnical 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.

Benefits

• 401(k).
• Dental Insurance.
• Health insurance.
• Vision insurance.
• We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
• The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.

Additional Responsibilities

• Participate in OP monthly team meetings and participate in team-building efforts.
• Contribute to OP technical discussions, peer reviews, etc.
• Contribute content and collaborate via the OP-Wiki/Knowledge Base.
• Provide status reports to OP Account Management as requested.

About Us

At OP, we help you harness the power of technology for maximum impact. A technology consulting and solutions company, we offer advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields including AI, cyber security, enterprise architecture, and beyond. For nearly two decades, we ve been challenging the status quo of the consulting industry serving up fresh, ingenious thinking through a radically lean structure. Together, this strategy delivers unprecedented performance at an unparalleled pace for faster results that propel your business forward.