Consultant

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.


Designation : Consultant

Location : Cary, North Carolina , United States

Experience : 7 to 10 years


Job Role :

100% Databricks-Native Architecture: Architect, build, and deploy an end-to-end, compound Generative AI platform built entirely within the client's Azure Databricks Lakehouse environment-avoiding external proprietary SaaS black-boxes.

Databricks Mosaic AI Suite: Drive AI development using the Databricks Mosaic AI stack (Mosaic AI Model Serving, Mosaic AI Agent Framework, Vector Search, and AI Gateway) to orchestrate multi-model generation and automated LLM-as-a-Judge validation.

Unified Data Governance via Unity Catalog: Enforce strict data security, column/row-level access controls, and full data lineage across all structured product catalogs, vector indexes, and LLM prompt tools using Unity Catalog.

Databricks Volumes for Unstructured Staging: Establish large-file ingestion pathways utilizing Databricks Volumes to parse and stage heavy offline brand guideline decks (>5 GB) into unstructured vector stores.


Responsibilities :


1. Onsite Client Engagement & Project Leadership

Act as the single point of contact for client Product Owners, Data Science Directors, and E-Commerce leads to gather and refine functional/technical requirements.

Own and facilitate daily stand-ups, weekly program updates, bi-weekly sprint planning, and monthly executive steering committee reviews.

Manage delivery cadence, scope alignment, risk escalation, and change-control processes on the ground.

Lead business user walkthroughs and User Acceptance Testing (UAT) sign-off sessions for AI platform releases.


2. Solution Architecture & Technical Delivery

Oversee the design and deployment of an end-to-end Agentic AI platform within the client's Azure Databricks workspace.

Architect multi-tier data ingestion pipelines in Databricks Auto Loader handling structured product master files, unstructured PDFs/PPTs (>5 GB), and third-party vendor APIs.

Enforce Unity Catalog governance, data lineage tracking, and interface-level pipeline transparency for business transparency.

Guide the offshore development team on building RAG frameworks, Vector Search indexing, and multi-model routing across Claude, GPT, and open-source model tiers.


3. AI Engine & Validation Framework Oversight

Direct the design of "LLM-as-a-Judge" automated validation scorecards evaluating generated copy across Brand Compliance, SEO/GEO/AEO, Quality, and Legal Claims.

Ensure implementation of structured JSON outputs (via Pydantic) to guarantee seamless downstream UI rendering and system stability.

Drive cost-optimization mechanisms, including model tiering, token caching, and spend-alert dashboards for client administrators.

Oversee the development of reusable "Skills Libraries" and prompt templates for one-click content adaptations.


4. Offshore Coordination & Quality Assurance

Bridge business requirements into detailed Jira user stories, data contracts, and technical specifications for the offshore engineering team.

Review PySpark notebooks, AI pipeline code, and SQL queries to ensure performance, security, and enterprise standards.

Ensure delivery of complete technical documentation packages, including Solution Architecture Documents (SAD), pipeline specs, user manuals, and code repository handovers.


Required skills :

Databricks (E2E) Execution is mandatory Databricks & Lakehouse Ecosystem: Deep expertise in PySpark, Delta Lake (Medallion Architecture), Auto Loader, Unity Catalog, and Databricks Volumes. Generative AI & Agentic Orchestration: Hands-on experience with LLM frameworks (LangChain, LangGraph, AutoGen), RAG pipelines, Vector Search, and prompt engineering. Client Management & Technical Leadership: Proven experience leading onsite client engagements, facilitating daily standups, weekly steering meetings, and technical walkthroughs. Python & SQL Mastery: Advanced proficiency in Python (including Pydantic, Pandas, REST APIs) and enterprise SQL optimization. Data Integration & ETL: Solid background in connecting PIM (e.g., Salsify), PLM/CAD data, and third-party REST APIs into centralized data lakes.


At LatentView Analytics, we value a diverse, inclusive workforce and provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual's race, colour, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.