Applied AI + NLP Engineer

Entegrata; Indianapolis (IN); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with employer match

Unlimited PTO & company holidays

Flexible remote work

Job summary

Entegrata, a venture-backed SaaS company in Indianapolis, seeks a senior Applied AI + NLP Engineer to turn a governed data platform into an enablement layer for a firm\'s AI strategy. You will ship conversational analytics, extract data from documents, and enable new legal-use cases on top of our semantic layer.

You will work at the intersection of data engineering, AI, and product, delivering guided, trustworthy AI capabilities for law firms.

Qualifications

• 5+ years of software engineering with hands-on AI/NLP/ML in production.
• Practical experience with LLMs: prompting, retrieval-augmented generation, agents, and tool use.
• Experience with information extraction, document parsing, classification or named entity recognition.
• Strong evaluation mindset: building test sets and measuring model and system quality.
• Solid SQL and understanding of structured data and semantic layers.
• Proficiency in Python and one of Go, .NET, or Node.js.
• Focus on accuracy, safety, and reliability in customer-facing AI.

Responsibilities

• Build systems translating natural language questions into deterministic analytical workflows over structured legal data.
• Define semantic models and metadata enabling LLMs to reason over data.
• Improve intent recognition, query planning, and ambiguity resolution for accurate responses.
• Develop AI agents to access, interpret, and synthesize data and legal content.
• Build orchestration logic selecting data sources, models, tools, and workflows for each request.
• Implement guardrails aligning AI responses with business definitions and semantic models.
• Create evaluation frameworks, benchmark datasets, and automated tests for quality and reliability.
• Collaborate with Data Engineering to expose metrics, dimensions, and relationships for AI consumption.
• Design AI pipelines transforming legal documents into structured data.
• Evolve data models capturing key concepts, relationships, and business meaning.
• Identify legal concepts, obligations, timelines, and terms to populate data models.
• Design confidence scoring, validation, and human review workflows.

Skills

Software engineering

Applied AI

NLP

ML in production

LLMs

Prompting

RAG

Agents

Tool use

Information extraction

Document parsing

NER

SQL

Semantic layers

Python

Go

.NET

Node.js

Accuracy & safety

Tools

Python

Go

.NET

Node.js

SQL

Azure

LIMs tooling

Job description

About Entegrata

Entegrata helps law firms turn data into decision-grade insights. Founded in 2023 and headquartered in Indianapolis, we are a venture-backed SaaS company delivering a turnkey, Azure-based data lakehouse platform purpose-built for law firms. Our platform consolidates siloed legal, operational, and financial data into a single governed source of truth, with AI-powered analytics on top. Our mission is to become the data platform of choice for the top law firms in the world.

The Role

Law firms are pouring both time and money into AI, and many efforts stall on the same point: the data underpinning the endeavor. Your job is to fix that.

As our first Applied AI + NLP Engineer, you build the intelligence that turns Entegrata's governed data platform into an enablement layer for a firm's entire AI strategy. You will ship the conversational analytics that let firm leaders interact with their data in plain English and get governed, accurate answers they can act on. In addition to helping unlock value related to structured data from firm systems, you will help us turn legal documents into discrete data. This distillation of documents will help our customers tap into key content with added precision, enabling new insights for customers. You will also build the retrieval and natural-language-to-query capabilities that help firms get more out of the AI tools they already run, and light up new business and practice of law use cases that were not possible before. Because this all sits on top of our governed semantic layer, accuracy, trust, and respect for firm data boundaries are non-negotiable.

This is a senior, hands-on role at the core of our AI enablement roadmap. You will need to be comfortable working where data engineering, AI and product intersect.

Key Responsibilities

AI for Structured Data & Analytics (Initial Focus)

• Build systems that translate natural language questions into deterministic analytical workflows and governed queries over structured legal data.
• Help define and implement semantic models and metadata that enable LLMs and AI agents to reason consistently over operational, business, and legal data.
• Improve intent recognition, query planning, and ambiguity resolution to deliver accurate, consistent responses-even when user requests are incomplete or underspecified.
• Develop AI agents capable of accessing, interpreting, and synthesizing structured data and legal content to answer complex business questions.
• Build orchestration logic that intelligently selects the appropriate data sources, models, tools, and workflows for each request.
• Implement guardrails that ensure AI responses align with governed business definitions, semantic models, and firm conventions.
• Build evaluation frameworks, benchmark datasets, and automated tests that continuously improve answer quality, determinism, and reliability.
• Collaborate with Data Engineering to expose governed metrics, dimensions, relationships, and business logic for AI consumption.

Document Intelligence & Knowledge Extraction

• Design and build AI pipelines that transform complex legal documents into structured, machine-understandable data.
• Help design and evolve legal data models that capture the key concepts, relationships, and business meaning contained within legal documents.
• Develop techniques to identify legal concepts, obligations, timelines, financial terms, parties, and other domain-specific information that populate and enrich those data models.
• Design confidence scoring, validation, and human review workflows that improve extraction quality and support continuous model refinement.

AI Platform Evolution

• Optimize AI workflows for quality, latency, scalability, and cost across the platform.
• Partner closely with Product, Data Engineering, and legal domain experts to translate customer needs into production AI capabilities.
• Stay current with advances in applied AI, LLMs, and agentic systems, bringing practical innovations into production where they create measurable customer value.

What Success Looks Like: 30-60-90 Days

First 30 Days | Learn and Contribute

• Ramp on the platform, semantic layer, and current AI capabilities and evaluation approach.
• Help create or improve a natural-language query or retrieval flow.

By 60 Days | Build and Improve

• Own an end-to-end AI capability, including its evaluation harness and quality metrics.
• Deliver the initial design framework for deconstructed legal documents.
• Measurably improve answer accuracy or reliability on a defined test set.

By 90 Days | Own and Lead

• Deliver production AI features with strong, measured quality and guardrails.
• Set a technical direction for a piece of the AI roadmap and drive it forward.
• Establish yourself as a trusted technical partner who can independently design, buils and improve AI capabilities across the Entegrata platform.

Required Qualifications

• 5+ years of software engineering, with hands-on experience building applied AI, NLP, or ML features in production.
• Practical experience with LLMs: prompting, retrieval-augmented generation, agents, and tool use.
• Experience with information extraction, document parsing, classification or named entity recognition.
• Strong evaluation mindset: building test sets and measuring model and system quality.
• Solid SQL and understanding of structured data and semantic layers.
• Proficiency in Python and one of Go, .NET, or Node.js.
• Focus on accuracy, safety, and reliability in customer-facing AI.

Preferred Qualifications

• Experience with natural-language-to-SQL or query generation over governed data.
• Familiarity with data lakehouse or BI platforms (Databricks, Snowflake, or Microsoft Fabric).
• Experience with vector / semantic search, embeddings, reranking and hybrid retrieval.
• Experience building pipelines and processing approaches for long-form or highly structured documents.
• Legal, finance, or professional services domain exposure.

Technology Stack

Python, LLM tooling, RAG, vector search, SQL, Azure, Go/.NET/Node.js.

Compensation And Benefits

Competitive salary, medical, dental, and vision insurance, 401(k) with employer match, unlimited PTO and company holidays, professional development support, and flexible remote work.

Equal Opportunity

Entegrata is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic.