Senior Manager Software Engineering, AI Experiences
Instacart
Senior Manager Software Engineering, AI Experiences
Job Description
Responsibilities
- Lead, coach, and develop a team of 10+ engineers building AI-powered shopping and merchant experiences across mobile and web, fostering an inclusive, high-trust culture.
- Own end-to-end delivery of AI features (e.g., conversational search, smart lists, meal planning, personalization), from roadmap and scoping to launch and iteration, anchored to clear OKRs.
- Provide technical leadership across LLM systems, including prompt orchestration, retrieval-augmented generation (RAG), safety/guardrails, online evaluation, and latency/cost optimization.
- Partner cross-functionally with Product, Design, Data Science, Research, and Operations; influence strategy and prioritization through clear communication and data-driven decision making.
- Establish engineering excellence: code quality, testing, observability, SLOs, incident response, on-call health, and privacy/security best practices for PII and model safety.
- Hire exceptional talent, manage performance, and create career growth paths; help shape the team’s operating model and rituals as we scale.
- Measure business impact via instrumentation and A/B testing; rapidly iterate based on insights to improve conversion, retention, and user satisfaction.
Required Qualifications
- 10+ years of professional software engineering experience, including 4+ years directly managing software engineers (hiring, performance management, and career development).
- Track record leading teams of 8+ engineers to deliver high-impact consumer or marketplace features in production.
- Hands-on experience building and shipping ML/AI-powered product experiences, including integrating modern LLMs or large-scale NLP systems in production (e.g., RAG, prompt engineering, safety/guardrails).
- Proficiency in at least one backend language (e.g., Python, Go, Java) and with a major cloud platform (AWS or GCP); strong SQL skills for data analysis and instrumentation.
- Experience designing, operating, and scaling services with clear SLOs, on-call ownership, observability, and incident response.
- Practical experience with experimentation platforms and A/B testing, defining success metrics, and making data-informed decisions.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Located in and eligible to work in the United States or Canada.
Preferred Qualifications
- Experience leading multiple teams or managing managers, including scaling an organization from early stages to 10+ engineers.
- Deep experience with LLM ecosystems: vector databases/embeddings, evaluation frameworks, hallucination mitigation, fine-tuning, or RLHF.
- Background in e-commerce, search/recommendations, ads, or large-scale consumer applications with millions of users.
- Experience optimizing LLM inference for cost, latency, and reliability; familiarity with model/provider evaluation and vendor management.
- Familiarity with security, privacy, and compliance considerations for AI systems (e.g., SOC 2, GDPR/CCPA) and safe AI practices.
- Advanced degree in Computer Science, Machine Learning, or related field.
Required Skills
- Software engineering
- Engineering management
- ML/AI-powered product experiences
- LLMs
- NLP systems
- RAG
- Prompt engineering
- Safety/guardrails
- Backend languages (Python, Go, Java)
- Cloud platforms (AWS, GCP)
- SQL
- SLOs
- Observability
- Incident response
- A/B testing
- Experimentation platforms
- Data analysis
- Instrumentation
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
- Flex First remote work policy
- Regular in-person events
Salary Range
$216000 - $289000 USD
Locations
- United States, United States
Salary
216,000 - 289,000 USD / yearly
Skills Required
- Software engineeringintermediate
- Engineering managementintermediate
- ML/AI-powered product experiencesintermediate
- LLMsintermediate
- NLP systemsintermediate
- RAGintermediate
- Prompt engineeringintermediate
- Safety/guardrailsintermediate
- Backend languages (Python, Go, Java)intermediate
- Cloud platforms (AWS, GCP)intermediate
- SQLintermediate
- SLOsintermediate
- Observabilityintermediate
- Incident responseintermediate
- A/B testingintermediate
- Experimentation platformsintermediate
- Data analysisintermediate
- Instrumentationintermediate
Required Qualifications
- 10+ years of professional software engineering experience, including 4+ years directly managing software engineers (hiring, performance management, and career development). (experience)
- Track record leading teams of 8+ engineers to deliver high-impact consumer or marketplace features in production. (experience)
- Hands-on experience building and shipping ML/AI-powered product experiences, including integrating modern LLMs or large-scale NLP systems in production (e.g., RAG, prompt engineering, safety/guardrails). (experience)
- Proficiency in at least one backend language (e.g., Python, Go, Java) and with a major cloud platform (AWS or GCP); strong SQL skills for data analysis and instrumentation. (experience)
- Experience designing, operating, and scaling services with clear SLOs, on-call ownership, observability, and incident response. (experience)
- Practical experience with experimentation platforms and A/B testing, defining success metrics, and making data-informed decisions. (experience)
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. (experience)
- Located in and eligible to work in the United States or Canada. (experience)
Preferred Qualifications
- Experience leading multiple teams or managing managers, including scaling an organization from early stages to 10+ engineers. (experience)
- Deep experience with LLM ecosystems: vector databases/embeddings, evaluation frameworks, hallucination mitigation, fine-tuning, or RLHF. (experience)
- Background in e-commerce, search/recommendations, ads, or large-scale consumer applications with millions of users. (experience)
- Experience optimizing LLM inference for cost, latency, and reliability; familiarity with model/provider evaluation and vendor management. (experience)
- Familiarity with security, privacy, and compliance considerations for AI systems (e.g., SOC 2, GDPR/CCPA) and safe AI practices. (experience)
- Advanced degree in Computer Science, Machine Learning, or related field. (experience)
Responsibilities
- Lead, coach, and develop a team of 10+ engineers building AI-powered shopping and merchant experiences across mobile and web, fostering an inclusive, high-trust culture.
- Own end-to-end delivery of AI features (e.g., conversational search, smart lists, meal planning, personalization), from roadmap and scoping to launch and iteration, anchored to clear OKRs.
- Provide technical leadership across LLM systems, including prompt orchestration, retrieval-augmented generation (RAG), safety/guardrails, online evaluation, and latency/cost optimization.
- Partner cross-functionally with Product, Design, Data Science, Research, and Operations; influence strategy and prioritization through clear communication and data-driven decision making.
- Establish engineering excellence: code quality, testing, observability, SLOs, incident response, on-call health, and privacy/security best practices for PII and model safety.
- Hire exceptional talent, manage performance, and create career growth paths; help shape the team’s operating model and rituals as we scale.
- Measure business impact via instrumentation and A/B testing; rapidly iterate based on insights to improve conversion, retention, and user satisfaction.
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
- general: Flex First remote work policy
- general: Regular in-person events
Tags & Categories
Senior Manager Software Engineering, AI Experiences
Instacart
Senior Manager Software Engineering, AI Experiences
Job Description
Responsibilities
- Lead, coach, and develop a team of 10+ engineers building AI-powered shopping and merchant experiences across mobile and web, fostering an inclusive, high-trust culture.
- Own end-to-end delivery of AI features (e.g., conversational search, smart lists, meal planning, personalization), from roadmap and scoping to launch and iteration, anchored to clear OKRs.
- Provide technical leadership across LLM systems, including prompt orchestration, retrieval-augmented generation (RAG), safety/guardrails, online evaluation, and latency/cost optimization.
- Partner cross-functionally with Product, Design, Data Science, Research, and Operations; influence strategy and prioritization through clear communication and data-driven decision making.
- Establish engineering excellence: code quality, testing, observability, SLOs, incident response, on-call health, and privacy/security best practices for PII and model safety.
- Hire exceptional talent, manage performance, and create career growth paths; help shape the team’s operating model and rituals as we scale.
- Measure business impact via instrumentation and A/B testing; rapidly iterate based on insights to improve conversion, retention, and user satisfaction.
Required Qualifications
- 10+ years of professional software engineering experience, including 4+ years directly managing software engineers (hiring, performance management, and career development).
- Track record leading teams of 8+ engineers to deliver high-impact consumer or marketplace features in production.
- Hands-on experience building and shipping ML/AI-powered product experiences, including integrating modern LLMs or large-scale NLP systems in production (e.g., RAG, prompt engineering, safety/guardrails).
- Proficiency in at least one backend language (e.g., Python, Go, Java) and with a major cloud platform (AWS or GCP); strong SQL skills for data analysis and instrumentation.
- Experience designing, operating, and scaling services with clear SLOs, on-call ownership, observability, and incident response.
- Practical experience with experimentation platforms and A/B testing, defining success metrics, and making data-informed decisions.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Located in and eligible to work in the United States or Canada.
Preferred Qualifications
- Experience leading multiple teams or managing managers, including scaling an organization from early stages to 10+ engineers.
- Deep experience with LLM ecosystems: vector databases/embeddings, evaluation frameworks, hallucination mitigation, fine-tuning, or RLHF.
- Background in e-commerce, search/recommendations, ads, or large-scale consumer applications with millions of users.
- Experience optimizing LLM inference for cost, latency, and reliability; familiarity with model/provider evaluation and vendor management.
- Familiarity with security, privacy, and compliance considerations for AI systems (e.g., SOC 2, GDPR/CCPA) and safe AI practices.
- Advanced degree in Computer Science, Machine Learning, or related field.
Required Skills
- Software engineering
- Engineering management
- ML/AI-powered product experiences
- LLMs
- NLP systems
- RAG
- Prompt engineering
- Safety/guardrails
- Backend languages (Python, Go, Java)
- Cloud platforms (AWS, GCP)
- SQL
- SLOs
- Observability
- Incident response
- A/B testing
- Experimentation platforms
- Data analysis
- Instrumentation
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
- Flex First remote work policy
- Regular in-person events
Salary Range
$216000 - $289000 USD
Locations
- United States, United States
Salary
216,000 - 289,000 USD / yearly
Skills Required
- Software engineeringintermediate
- Engineering managementintermediate
- ML/AI-powered product experiencesintermediate
- LLMsintermediate
- NLP systemsintermediate
- RAGintermediate
- Prompt engineeringintermediate
- Safety/guardrailsintermediate
- Backend languages (Python, Go, Java)intermediate
- Cloud platforms (AWS, GCP)intermediate
- SQLintermediate
- SLOsintermediate
- Observabilityintermediate
- Incident responseintermediate
- A/B testingintermediate
- Experimentation platformsintermediate
- Data analysisintermediate
- Instrumentationintermediate
Required Qualifications
- 10+ years of professional software engineering experience, including 4+ years directly managing software engineers (hiring, performance management, and career development). (experience)
- Track record leading teams of 8+ engineers to deliver high-impact consumer or marketplace features in production. (experience)
- Hands-on experience building and shipping ML/AI-powered product experiences, including integrating modern LLMs or large-scale NLP systems in production (e.g., RAG, prompt engineering, safety/guardrails). (experience)
- Proficiency in at least one backend language (e.g., Python, Go, Java) and with a major cloud platform (AWS or GCP); strong SQL skills for data analysis and instrumentation. (experience)
- Experience designing, operating, and scaling services with clear SLOs, on-call ownership, observability, and incident response. (experience)
- Practical experience with experimentation platforms and A/B testing, defining success metrics, and making data-informed decisions. (experience)
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. (experience)
- Located in and eligible to work in the United States or Canada. (experience)
Preferred Qualifications
- Experience leading multiple teams or managing managers, including scaling an organization from early stages to 10+ engineers. (experience)
- Deep experience with LLM ecosystems: vector databases/embeddings, evaluation frameworks, hallucination mitigation, fine-tuning, or RLHF. (experience)
- Background in e-commerce, search/recommendations, ads, or large-scale consumer applications with millions of users. (experience)
- Experience optimizing LLM inference for cost, latency, and reliability; familiarity with model/provider evaluation and vendor management. (experience)
- Familiarity with security, privacy, and compliance considerations for AI systems (e.g., SOC 2, GDPR/CCPA) and safe AI practices. (experience)
- Advanced degree in Computer Science, Machine Learning, or related field. (experience)
Responsibilities
- Lead, coach, and develop a team of 10+ engineers building AI-powered shopping and merchant experiences across mobile and web, fostering an inclusive, high-trust culture.
- Own end-to-end delivery of AI features (e.g., conversational search, smart lists, meal planning, personalization), from roadmap and scoping to launch and iteration, anchored to clear OKRs.
- Provide technical leadership across LLM systems, including prompt orchestration, retrieval-augmented generation (RAG), safety/guardrails, online evaluation, and latency/cost optimization.
- Partner cross-functionally with Product, Design, Data Science, Research, and Operations; influence strategy and prioritization through clear communication and data-driven decision making.
- Establish engineering excellence: code quality, testing, observability, SLOs, incident response, on-call health, and privacy/security best practices for PII and model safety.
- Hire exceptional talent, manage performance, and create career growth paths; help shape the team’s operating model and rituals as we scale.
- Measure business impact via instrumentation and A/B testing; rapidly iterate based on insights to improve conversion, retention, and user satisfaction.
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
- general: Flex First remote work policy
- general: Regular in-person events
Tags & Categories