AI Software Engineer (Backend) - Multiple Levels (Mid-Senior)
About the Company
A rapidly growing AI technology company based in San Francisco, revolutionizing the logistics industry by automating manual workflows with agentic AI. Their leadership team previously scaled a last‑mile logistics startup to 450 employees and a $2.1 billion acquisition by Shopify. Currently, they have raised $25 million in Series A funding to tackle freight brokerage, trucking, warehousing, and beyond.
Mission & Impact
By embedding AI agents into Transportation Management Systems, they eliminate repetitive tasks such as email correspondence, phone‑based shipment tracking, and invoicing—driving efficiency, reducing errors, and empowering brokers to focus on high‑value work.
Role Overview
Seeking hands‑on engineers who have built products from 0→1, possess strong systems‑design skills, and are passionate about AI‑driven applications. Responsibilities include designing, developing, testing, deploying, and maintaining core backend infrastructure that powers LLM workflows, voice‑AI skills, and integrations with enterprise logistics platforms.
Key Responsibilities
- Build and scale microservices that orchestrate AI agents for logistics workflows (proof‑of‑delivery, track‑and‑trace, carrier selection).
- Develop "skills" libraries enabling agents to send emails, place calls, and interact via chat platforms.
- Integrate with brokers’ TMS platforms via REST APIs, message queues (SQS/SNS), and webhooks.
- Implement voice‑AI pipelines for automated outbound calls and real‑time user interactions.
- Collaborate in fast‑paced sprints, iterating on features, refining system performance, and ensuring reliability through comprehensive monitoring and testing.
Ideal Candidate Profile
- Technical Expertise: 4+ years of backend development using TypeScript, Python, or JavaScript.
- 0→1 Experience: Demonstrated ability to ship new products or major features end‑to‑end.
- Systems Design: Strong at framing requirements, diagramming architecture, evaluating trade‑offs (scalability, failure modes, multi‑tenancy), and articulating design decisions.
- Cloud Proficiency: Hands‑on AWS experience (SQS, SNS, RDS, Lambda, ECS/EKS, Infrastructure as Code).
- AI/LLM Integration: Experience building or deploying Retrieval‑Augmented Generation (RAG) pipelines, agentic workflows, or voice‑AI features using OpenAI, Anthropic, Llama, Eleven Labs, etc.
- Startup Mindset: Thrives in scrappy environments, communicates clearly with cross‑functional partners, and takes full ownership of deliverables.
Compensation & Benefits
- Competitive base salary with equity package
- Comprehensive health, dental, and vision coverage
- Unlimited PTO and flexible hybrid schedule
- 401(k) plan
Candidates energized by AI, curious by nature, and eager to make a tangible impact on a complex industry are encouraged to apply.
Contact
Send an email to ellie.palmer@thirdrepublic.com to apply.
Job Highlights
Qualifications
- Technical Expertise: 4+ years of backend development using TypeScript, Python, or JavaScript
- 0→1 Experience: Demonstrated ability to ship new products or major features end-to-end
- Systems Design: Strong at framing requirements, diagramming architecture, evaluating trade-offs (scalability, failure modes, multi-tenancy), and articulating design decisions
- Cloud Proficiency: Hands-on AWS experience (SQS, SNS, RDS, Lambda, ECS/EKS, IaC)
- AI/LLM Integration: Experience building or deploying Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, or voice-AI features using OpenAI, Anthropic, Llama, Eleven Labs, etc.
- Startup Mindset: Thrives in scrappy environments, communicates clearly with cross-functional partners, and takes full ownership of deliverables
Benefits
- Compensation & Benefits
- Competitive base salary with equity package
- Comprehensive health, dental, and vision coverage
- Unlimited PTO and flexible hybrid schedule
- 401(k) plan
Responsibilities
- Building and maintaining core backend infrastructure for AI workflows.
- Designing, developing, and scaling microservices for logistics operations.
- Creating libraries for AI skills such as email, calls, and chat interactions.
- Integrating with TMS platforms via APIs, message queues, and webhooks.
- Developing voice‑AI pipelines for outbound calls and interactions.
- Collaborating in agile sprints to enhance system performance and reliability.