SpotDraft is on a mission to help legal and business teams move faster, together. Our AI-powered contracting platform is redefining how companies manage contracts, and our story deserves to be told in creative, human, and memorable ways.
SpotDraft is revolutionizing legal operations with AI-powered tools that help legal teams work faster and smarter. Our flagship products leverage cutting-edge LLM technology to automate routine legal work and accelerate contract review.
Sidebar is an AI-powered team of legal assistants that handles routine legal work—from contract analysis and legal research to compliance tracking and drafting SpotDraft. It tackles everything beyond contracts, including policy questions, regulatory compliance, and strategic advice SpotDraft, learning from your organization's knowledge to become a specialized legal co-pilot.
VerifAI is an AI contract review tool that works as a Microsoft Word add-in, helping legal teams review contracts up to 70% faster with SpotDraft. It uses generative AI to check contracts against personal or organizational guidelines and answer open-ended questions SpotDraft, automatically flagging deviations and suggesting improvements.
We're looking for a Backend Engineer to join the AAI Pod — the team building SpotDraft's AI-powered product capabilities, including data/text extraction, contract intelligence, and LLM-driven features layered on our core contracting platform. You'll help architect, build, and scale backend systems that power these AI features end-to-end, working closely with Product, Engineering, and AI teams to ship high-impact capabilities that our customers directly experience.
This role sits at the intersection of strong backend fundamentals and applied AI — you won't just be calling an API, you'll be designing the systems (extraction pipelines, RAG architectures, orchestration layers) that make AI features reliable and scalable in production.
What you'll do
System Design & Architecture
Design and build scalable backend systems for AI-powered features, with a strong focus on reliability and performance
Own end-to-end system design (HLDs & LLDs) for extraction pipelines and AI feature integration
Make thoughtful trade-offs balancing speed, scalability, and maintainability in systems that call LLMs or process high volumes of documents/text
AI & Extraction Systems
Build and operate data/text extraction pipelines that power downstream AI features
Design and implement RAG pipelines, LLM integrations, or agentic workflows as part of product features
Own the reliability and cost-efficiency of AI-integrated systems — caching, fallback handling, and failure recovery for LLM-dependent services
Product & Engineering Collaboration
Work closely with Product, Design, and AI teams to ship impactful features
Translate ambiguous product requirements into clear technical solutions
Participate in cross-functional discussions and influence product direction
Execution & Ownership
Own features and systems end-to-end — from ideation to production and beyond
Build systems from scratch and evolve them as they scale
Take accountability for reliability, performance, and uptime of owned systems
Team & Culture Contribution
Contribute to hiring by participating in interviews and candidate evaluation
Mentor junior engineers and raise the overall engineering bar
Bring a strong "builder's mindset" with a bias for action and problem-solving
Must haves
4–7 years of experience in backend/software engineering (minimum 4–5 years)
Strong backend engineering fundamentals — proven experience architecting and building scalable products/features end-to-end (not just feature-level execution)
Hands-on experience with system design (HLD & LLD)
AI/ML exposure — either has built/implemented a RAG pipeline, or has integrated/used LLMs in a production application
Experience with data or text extraction pipelines — this is core to the pod's work, not a peripheral skill
Should haves
Distributed systems experience — queues, async processing, caching
Familiarity with vector databases / embeddings (Pinecone, Weaviate, pgvector, etc.)
Experience working in cross-functional teams (Product, Design, AI)
Track record of ownership — building, scaling, and maintaining systems independently
Nice to haves
Python or Go
Apache Beam or similar large-scale data processing frameworks
Prior experience in document-heavy or NLP-adjacent products (legal tech, fintech, OCR, search)
Prior experience in startup environments or fast-paced teams
Brilliant teammates—Work with some of the sharpest minds in legal tech.
Expand your network—Interact with top founders, investors, and industry leaders.
Real impact—Take ownership of projects and see your work in action.
Big goals, bold moves—We trust you to deliver, innovate, and push boundaries.
Our business is to delight Customers
Be Transparent. Be Direct
Be Audacious
Outcomes over everything else
Elevate each other
Be Passionate. Take Ownership.
Be 1% better every day
All candidates’ personal data shared during the recruitment process will be handled with utmost confidentiality and used solely for hiring purposes, in line with applicable data protection regulations.
- SpotDraft is an equal-opportunity employer. Candidates will not be discriminated against based on race, ethnicity, color, religion, caste, sex, gender identity, sexual orientation, national origin, veteran, or disability status
