Software Engineer, Level 6
LawPay
AWSCloudPython
Salary
💰 $170,000 - $200,000 per year
Job Level
Senior
Tech Stack
AWSCloudPython
About the role
- Lead the 0→1 buildout and 1→n scaling of AI capabilities at Optimal Dynamics; set direction and establish engineering standards.
- Own RAG initiatives end-to-end from problem framing and data readiness through prototyping, iteration, and production launch.
- Establish foundational components and practices for document processing, indexing, retrieval, orchestration, and evaluation.
- Select tools and approaches that balance quality, cost, and speed.
- Build reliable services and APIs that are observable, secure, and designed for scale in a cloud environment.
- Define success metrics (quality, latency, cost, safety) and drive continuous improvement via experimentation and data-driven decisions.
- Create durable team assets (playbooks, test harnesses, checklists, and documentation) to make RAG development repeatable across products.
- Collaborate cross-functionally with Product, Data/ML, Engineering, and GTM to translate ambiguous needs into shippable capabilities with clear business impact.
- Mentor teammates and contribute to a strong engineering culture around AI systems and responsible deployment.
- Make key architecture and tooling choices and evolve them as the team learns.
Requirements
- 4+ years of proven industry experience building and operating backend, platform, or data services at production scale
- Bachelor's degree in Computer Science, Electrical Engineering, Operations Research, or Mathematics/Physics
- Proven track record delivering data or ML-powered features end-to-end (Discovery/Prototyping > Launch > Iteration)
- Python Proficiency - you write well-tested & maintainable code.
- API design expertise and experience with cloud services (preferably AWS)
- Familiarity with information retrieval concepts and grounding AI systems in trustworthy data.
- Comfort setting technical direction, selecting tools, and establishing engineering best practices for AI-focused builds.
- Senior, hands-on engineer who can take a fuzzy problem from discovery to reliable production outcomes.
- Pragmatic: balance quality, cost, speed, and risk to ship value iteratively.
- Communicative: ability to align stakeholders and translate complex technical ideas into clear decisions.
- Operational Owner: cares about reliability, observability, and measurable impact on customers and the business.
- Nice to have: Experience introducing retrieval-augmented or knowledge-grounded AI capabilities in a product or platform context.
- Nice to have: Exposure to evaluation methodologies for AI systems (quality, latency, cost, safety) and running experiments/A-B tests.
- Nice to have: Background working with unstructured data pipelines, indexing, and search, whether homegrown or via managed services.
- Nice to have: Experience mentoring engineers, uplifting practices, and creating reusable playbooks and templates.
- Nice to have: Experience in the transportation, logistics, or broader supply chain industry.
- Nice to have: Customer-facing collaboration comfort: gathering requirements, scoping MVPs, and measuring ROI post-launch.
