DecoverAI

Legal Intelligence Simplified. DecoverAI is the first Legal Intelligence Platform founded in 2024 and headquartered in Washington, D.C., that created the 360° Legal Brain™ - an AI-powered end-to-end…

decover.ai

DecoverAI

decover.ai

HQUS

Team Size8

Open JobsUnknown

Total Funding-

Latest FundraiseUnknown

TL;DR

Founded: 2024

Headquarters: Washington, D.C., United States

Product: AI-powered eDiscovery and document-review platform (Gambit, Sage/Agora)

Founders: Ravi Tandon; Janar Ramalingam; Kevin J. Van Horn

Funding: Seed round led by Leo Capital (Jul 30, 2024)

Company Overview

Problem Domain

Legal technology: eDiscovery, document review, legal research, and litigation support.

Founded

2024

Industry

LegalTech

Funding Track Record

Seed- 2024-07-30

Investor Signal

“Seed led by Leo Capital”

Join the Team

Founding Engineer

On-SiteBengaluru, Karnataka, IN

On-Site • Bengaluru, Karnataka, IN

We need a founding engineer who can own and build our entire AI platform end-to-end: from LLM pipelines and evaluation frameworks to scalable backend infra and polished product interfaces. You'll be the engineer who turns research-grade AI into production-grade legal intelligence.

Litigating attorneys drown in millions of pages of case documents, precedents, and filings. Existing tools are keyword searches slapped onto PDFs. We're building an AI system that actually understands legal reasoning and delivers deep, actionable insights in seconds.

Responsibilities

Startup jobs. A lot of them.

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AI Platform and Pipelines: Design and build production RAG systems, agentic workflows, and LLM orchestration layers. Pick the right models, chain them, ground them.

Evals and Model Quality: Build rigorous evaluation frameworks. Define metrics that matter, run systematic benchmarks, and continuously improve model accuracy, latency, and cost.

Scalable Infra: Architect backend services (APIs, queues, vector stores) that handle millions of legal documents without falling over. Own deployment, monitoring, and cost optimisation on cloud (AWS/GCP).

Product Engineering: Ship user-facing features with React/Next.js . You care about what the attorney actually sees and uses, not just what the model outputs.

Data and Embeddings: Work with massive structured and unstructured legal datasets. Build and maintain embedding pipelines, chunking strategies, and retrieval infrastructure.

MLOps and Lifecycle: Own the full model lifecycle: fine-tuning, deployment, A/B testing, monitoring, and rollback.

5+ years shipping production software; strong Python plus at least one of Go, Rust, or Kotlin.
Hands-on LLM experience: you've built real applications against OpenAI, Anthropic, or open- source models (not just called an API once).
Deep understanding of RAG architectures, prompt engineering, embeddings, and retrieval systems.
Solid backend engineering: APIs, microservices, distributed systems, SQL/NoSQL databases.
Cloud deployment experience (AWS/GCP/Azure), you've scaled services, not just deployed demos.
Strong CS fundamentals: data structures, algorithms, system design.
Frontend proficiency: React.js / Next.js or equivalent. You can build an entire AI application, not just a backend.

Experience with vector databases (Pinecone, Weaviate, FAISS, Qdrant).
MLOps tooling: MLflow, Airflow, Kubeflow, or similar.
Real-time data pipelines or streaming systems.

This job was posted by Hema Chandrashekar from DecoverAI.

DecoverAI

DecoverAI

TL;DR

Company Overview

Problem Domain

Founded

Industry

Funding Track Record

Investor Signal

Founders

What we do

Join the Team

Founding Engineer

Startup jobs. A lot of them.

Frontend Developer

Mobile Developer

Software Engineer

Frontend Developer

AI Researcher

Software Engineer

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