Senior Software Engineer - Delivery Intelligence
Team: Engineering
Location: Philadelphia, PA, Miami, FL
Commitment: Full Time
Workplace Type: hybrid
What You Bring
- 5+ years of software engineering experience, with meaningful work on optimization, logistics, marketplace dynamics, or applied ML systems.
- Hands-on experience building AI agents, LLM-powered workflows, or autonomous decision-making systems (not just chatbots—systems that take action and drive measurable customer outcomes).
- Strong fundamentals in algorithms, data structures, and system design. Comfortable owning services end-to-end, from database schema to deployment pipeline.
- Proficiency in Python, Go, or TypeScript, with experience in ML frameworks (PyTorch, scikit-learn) and data tools (SQL, Spark, dbt).
- Experience with real-time systems, event-driven architectures, or streaming platforms (Kafka, Flink, Kinesis).
- A customer-obsessed mindset. You naturally think about how your technical decisions affect the end user and make trade-offs that protect the customer experience.
- A bias toward shipping. You prototype quickly, validate with data, and iterate relentlessly. You are energized by ambiguity and thrive when the solution space is wide open.
Nice to Have
- Background in operations research, combinatorial optimization, or vehicle routing problems (VRP/CVRP).
- Experience with multi-agent systems, reinforcement learning, or simulation environments for logistics.
- Experience designing gamification systems, loyalty programs, or behavioral nudge frameworks in consumer or gig-economy products.
- Familiarity with delivery or gig-economy platforms and the nuances of driver supply-demand dynamics and retention strategies.
- Prior work with geospatial data, mapping APIs, or travel-time estimation models.
Build AI Agents for Delivery Optimization
- Design, build, and deploy autonomous AI agents that make real-time decisions about driver pay, order batching, route sequencing, and delivery time estimation—always optimizing for the fastest, most reliable customer experience.
- Develop agent architectures that combine LLM reasoning with structured optimization (linear programming, simulation) to solve multi-objective logistics problems.
- Create feedback loops where agents learn from delivery outcomes, driver behavior, and customer satisfaction signals to continuously improve performance.
- Build customer-facing intelligence: AI-powered ETA models that set accurate expectations, proactive delay notifications, and smart order prioritization that protects the customer promise.
Optimize Driver Pay & Incentive Models
- Engineer dynamic pay systems that balance driver earnings, delivery speed, and unit economics—ensuring Gopuff is the most attractive platform for drivers while hitting margin targets.
- Build experimentation frameworks to A/B test pay structures, bonus triggers, and incentive timing across markets and demand scenarios.
- Develop models that predict driver supply elasticity and optimize incentive spend across peak, off-peak, and surge conditions.
Design Driver Gamification & Engagement Systems
- Architect gamification engines that drive desired behaviors: achievement systems, streaks, leaderboards, tier-based rewards, and milestone bonuses that keep drivers engaged and performing at their best.
- Build AI-powered personalization that tailors challenges and incentives to individual driver patterns—the right nudge, at the right time, for the right driver.
- Develop real-time progress dashboards and in-app experiences that give drivers visibility into their earnings trajectory, performance rank, and next reward milestone.
- Instrument and analyze gamification effectiveness: measure impact on shift coverage, delivery speed, customer ratings, and driver satisfaction using rigorous experimentation.
Build for Driver Retention & Lifetime Value
- Develop predictive churn models that identify at-risk drivers before they leave, and trigger automated retention interventions (targeted bonuses, schedule flexibility, personalized outreach).
- Build onboarding optimization systems that reduce time-to-first-delivery and accelerate new drivers to peak performance through guided AI coaching.
- Design loyalty and tenure reward programs that increase long-term driver commitment while improving delivery quality for customers.
- Analyze the full driver lifecycle—acquisition, activation, engagement, retention—and build data products that give Operations teams actionable intelligence on driver health across every market.
Reduce Delivery Times at Scale
- Own the delivery time prediction pipeline: build and refine ML models that estimate prep time, transit time, and total delivery duration with high accuracy—because an accurate ETA is one of the strongest drivers of customer trust.
- Architect systems for intelligent order dispatching—matching orders to drivers based on proximity, capacity, route efficiency, and predicted completion time.
- Identify and eliminate bottlenecks across the fulfillment-to-doorstep chain using data-driven analysis and automated anomaly detection agents.
Ship Production Systems
- Write production-grade code in Python, Go, or TypeScript. Design APIs, data pipelines, and microservices that handle thousands of delivery decisions per minute.
- Collaborate with Data Science, Operations, and Product teams to translate business goals into technical solutions with clear success metrics tied to customer outcomes.
- Champion engineering excellence: code reviews, testing, observability, and documentation that keep the team moving fast without breaking things.
Compensation
- Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, interview performance, and market conditions. These ranges may be modified in the future. Exceptions may be made for exceptional individuals. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
- This role is eligible for a discretionary annual cash bonus and participation in Gopuff’s equity incentive plan.
- Hybrid Base Salary Range: $175,000 - $195,000
- Remote Base Salary Range: $155,000 - $175,000
Benefits Overview
- Medical/Dental/Vision Insurance
- 401(k) Retirement Savings Plan
- HSA or FSA eligibility
- Long and Short-Term Disability Insurance
- Mental Health Benefits
- Fitness Reimbursement Program
- 25% employee discount & FAM Membership
- Flexible PTO
- Group Life Insurance
- EAP through AllOne Health (formerly Carebridge)
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