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.
As a Junior Applied AI Engineer, you'll help build and maintain the production AI systems powering our legal-tech products. Working alongside senior engineers, you'll contribute to distributed AI services that process large volumes of legal documents, support multi-agent architectures, and help optimize LLM performance for accuracy, speed, and cost in our mission-critical SaaS environment.
Build AI Features
Implement and iterate on AI features using transformer-based architectures and prompt engineering for legal document workflows (summarization, clause extraction, document comparison, drafting assistance)
Contribute to agentic systems (ReAct-style flows, tool/function calling, multi-turn reasoning) under the guidance of senior engineers
Write and refine prompts, and help maintain prompt libraries and versioning
Support RAG & Context Systems
Help build and maintain retrieval pipelines: chunking strategies, hybrid search (BM25 + dense embeddings), and reranking for legal documents
Assist in building retrieval-grounded generation pipelines and tuning context window usage
Work with vector databases (Pinecone, Weaviate, Qdrant, or pgvector) to support semantic search features
Contribute to Infrastructure & Performance
Help build and maintain API services that call LLM providers (OpenAI, Anthropic, Google Gemini), including retry logic, rate limiting, and fallback handling
Support inference optimization efforts: caching, batching, and monitoring latency/cost
Write clean, tested, production-grade Python code within existing service architectures
Support Quality & Reliability
Help build evaluation scripts and test datasets to measure model output quality (accuracy, hallucination rate, relevance)
Assist with LLM-as-judge pipelines and human-in-the-loop labeling workflows
Participate in A/B testing of prompts, models, and configurations
MLOps & Observability
Support CI/CD pipelines for AI feature deployment (containerization, basic Kubernetes usage)
Help maintain monitoring dashboards for latency, token usage, error rates, and cost per request
Assist in debugging production issues using logs, traces, and dashboards
Must Have
Upto 3 years of experience in software/ML engineering, with at least some hands-on exposure to LLM-based systems
Working experience integrating LLM APIs (GPT-4, Claude, Gemini, or Llama) — prompt engineering, function calling, or basic fine-tuning
Know-how of context engineering — structuring, trimming, and managing what gets passed into the model's context window across a workflow
Understanding of agent loops and graphs — how agentic control flow works (e.g. ReAct-style loops, state graphs, conditional branching between steps/tools)
Hands-on experience building agentic workflows — chaining tool calls, managing state across turns, and handling multi-step reasoning
Experience building or contributing to eval systems — writing test cases, scoring outputs, and tracking quality/regression over time
Solid Python skills with an understanding of core software engineering practices (testing, version control, code review)
Foundational understanding of transformer architectures, embeddings, and how LLMs work
Some exposure to vector databases and semantic search concepts
Familiarity with async programming and API frameworks (FastAPI or similar)
Basic understanding of data structures, algorithms, and complexity
Comfort working in a fast-paced environment and learning quickly from senior engineers and code reviews
Good to Have
Exposure to agentic frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, or similar)
Exposure to text extraction and text wrangling in current/prior work (parsing PDFs, OCR output cleanup, handling messy or unstructured text)
Experience with Docker and basic CI/CD pipelines
Familiarity with cloud platforms (AWS, GCP, or Azure)
Any experience with evaluation frameworks, synthetic test data, or A/B testing for ML systems
Interest in or coursework related to document/multi-modal AI (OCR, layout analysis, vision-language models)
A personal project, hackathon, or open-source contribution involving LLMs or RAG systems
This role is designed to grow into a mid-level/Applied AI Engineer position, with mentorship from senior team members on distributed systems design, advanced RAG architecture, and large-scale inference optimization.
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
