Consultant AI & Data Engineer

SUMMARY As a Consultant AI & Data Engineer, you will design, develop, and deploy AI solutions that survive real client environments. That means navigating imperfect data, complex workflows, and leaders seeking confidence that AI solutions will be adopted and drive value. This role is for an engineer with systems depth, that can take AI from an interesting idea to practical operational tooling. Key areas include RAG, document processing, evaluations, observability, deployment, and integration patterns. You will be hands‑on, designing and delivering features and applications and serving as a technical voice in client conversations and with internal leadership. YOU WILL Translate ambiguous business problems into AI solutions, features, and tools that clients can adopt, deploy, and maintain with confidence. Lead and facilitate discovery conversations and shape solution design alongside clients, solution architects, and delivery leads. Build RAG, document AI, and AI‑enabled systems end‑to‑end: ingestion, chunking and layout decisions, retrieval design, vector and metadata schemas, prompt and context engineering, post‑processing, and evaluation. Define and run evaluation frameworks, benchmark against industry datasets, design reliability diagnostics and perform failure analysis to make decisions about models, retrieval strategies, and processing pipelines. Translate operational processes into structured and/or agentic AI workflows, designing human‑in‑the‑loop and explainable escalation patterns for sensitive tasks where AI/automation alone is insufficient. Stand up the observability needed to trust a system in production, including tracing, output capture, feedback loops, and monitoring for performance degradation. Mentor junior engineers, review their code, and raise the technical bar of the team. Present work and facilitate decision‑making sessions with client stakeholders with clarity and confidence, including PowerPoint presentations. IDEALLY, WE'D LIKE We are looking for demonstrated ability to design, develop, and deploy AI‑enabled solutions. The ideal candidate can showcase delivery from concept through to production and provide evidence of strong stakeholder communication. Experience 1–2 years in AI or data science roles, with 2–3 years in technical roles overall preferred. Bachelor's degree in computer science, data science, or a relevant field, or equivalent professional experience. Engineering fundamentals Writing‑level proficiency in Python and SQL (not just reading or generating code). Fluent use of AI coding tools with disciplined practices around trustworthy, human‑reviewed output. Working proficiency with data warehousing, integrations, APIs, and software development. Working command of Git, Docker, and CI/CD. AI engineering depth RAG fluency beyond top‑k: you have designed retrieval strategies, evaluated them, understood tradeoffs, and improved/mitigated them. Vector database experience at the schema‑design level: organization, metadata, hybrid retrieval, and tradeoffs. Document processing across text, images, and tables, with judgment for when to reach for which chunking, layout, or extraction approach. Experience designing evaluation frameworks and using them to drive decisions, including production readiness and evidence‑based improvements. Comfort with NoSQL stores, document versioning, and turning unstructured files into structured knowledge assets. Awareness of how data quality, drift, and edge cases break AI systems, and the patterns to mitigate them in imperfect environments. Comfort with data cleansing, transformation, and normalization techniques, including both structured and unstructured formats. Delivery and consulting skills Background in client‑facing or delivery‑oriented work including interpreting stakeholder needs and delivered a working solution at the end. Strong communication skills and effective with PowerPoint to present technical work to both technical and non‑technical stakeholders. Sound judgment in ambiguous problem spaces, able to make sensible assumptions, document them, and revisit them as patterns emerge. Commitment to staying abreast of latest advancements in applied AI. Cloud Working exposure to at least one of Azure, GCP, or AWS. Nice to Have Experience with LangGraph, LangChain, or comparable agent frameworks. Graph databases and ontology design. ML/NLP background is useful. Hands‑on time in Databricks, Snowflake, or Salesforce ecosystems. Prior experience in consulting environment. Recruiting information Applicants must be authorized to work in the United States, without the need for visa sponsorship by North Highland. Work visa sponsorship will not be provided, either now or in the future, for this position. North Highland is an equal opportunity employer, and we adhere to all applicable laws and regulations to ensure a fair and equitable workplace. All qualified applicants will receive fair and impartial consideration without regard to race, color, sex, gender identity, religion, national origin, age, sexual orientation, disability, veteran status, or any other characteristic protected by law. We handle all information in accordance local privacy standards and maintain strict confidentiality. #J-18808-Ljbffr North Highland