Software Development Engineer - BE (AI POD)

We're looking for an SDE II (BE) to join the AAI Pod, the team-building spot. Draft's AI-powered product capabilities include 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, and orchestration layers) that make AI features reliable and scalable in production.

The candidate will have responsibilities across the following functions:

System Design and 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 and 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 and 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, including caching, fallback handling, and failure recovery for LLM-dependent services.

Product and 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 and 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 the reliability, performance, and uptime of owned systems.

Team and 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.

Requirements:

• 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 and 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 have:

• 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 have:

• Experience in 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.