AI & Data Intelligence Engineer
Equinox Hcp Llp · Remote · remote · Posted 1d ago
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About this role
AI & Data Intelligence Engineer EquiSight
Location: Mumbai, India / Remote | Full-Time
Role Overview
Lead the accuracy, prompt architecture and statistical methodology engine for EquiSight, Equinox’s enterprise solution for job architecture and design, compensation studio and pay equity compliance. Work alongside our data architect, development team and domain experts to manage language-model pipelines, structured schema enforcement, versioned prompt templates and Python statistical algorithms.
Key Responsibilities
- Author, maintain, enhance and version-control EquiSight’s prompt templates.
- Enforce structured outputs using JSON Schema and Pydantic; route low-confidence or failed outputs to automated retries or human review.
- Manage AI Gateway logging of token usage, model parameters, confidence scores and verbatim evidence citations.
- Co-own the pure-Python analytics engine with the data architect and maintain statistical validation harnesses against reference datasets.
- Keep natural-language parsing/drafting separate from deterministic arithmetic, scoring and legal threshold checks.
- Pin methodology versions, prompt templates and model parameters in Git for auditability.
Technology Stack
Anthropic Claude via Microsoft Foundry in Azure EU; JSON Schema, Pydantic, Jinja2; Python 3.11+, statsmodels, scipy, numpy, pandas; OLS regression, Gelbach decomposition and robust covariance estimation; pytest, DeepEval/Promptfoo; Git/GitHub. Shared touchpoints include Celery/Redis task payloads and PostgreSQL datasets. Full-stack web development and cloud infrastructure provisioning are handled by the development partner.
Qualifications
Bachelor’s or Master’s in Data Science, Computer Science, AI/ML, Quantitative Economics or a related technical/quantitative field. Hands-on LLM prompt engineering and orchestration, advanced structured output validation, strong Python/statistics, and proven evaluation-harness experience to measure drift, citation accuracy and hallucination resistance.
Preferred: compensation analytics, job evaluation, pay equity or workforce analytics; familiarity with EU AI Act and Pay Transparency Directive or equivalent regional legislation. Backed by practical engineering and statistical rigor.
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