Instacart
Senior Software Engineer, AI Productivity
Vaga remota de Software Engineering com fit claro de localização do candidato.
PublicadaAdicionada recentemente
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Canadá
Resumo da vaga
Senior Software Engineer, AI Productivity
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
About the Job
- Design, build, and operate AI-powered services and internal applications—such as code and test assistants, knowledge search, and intelligent chat workflows—that improve developer and operator productivity at scale.
- Implement robust back-end services in languages such as Python, Go, or Java; integrate foundation models via APIs and open-source frameworks; and apply techniques like retrieval-augmented generation and vector search where appropriate.
- Own projects end-to-end, including requirements, technical design, implementation, testing, deployment, observability, on-call participation, and iterative improvements focused on reliability, latency, and cost efficiency.
- Partner with Developer Platform, ML Platform, Security, and Legal to ensure safe and compliant AI usage, including data governance, guardrails, content/prompt safety, and privacy-by-design.
- Define and track success with clear metrics (e.g., adoption, task completion time, DORA/SPACE signals, satisfaction), and run experiments and A/B tests to validate impact and guide iteration.
- Create and maintain shared tooling, libraries, and documentation that raise the bar for applied AI development across Instacart, and mentor teammates on best practices in this fast-paced, evolving space.
Minimum Qualifications
- 5+ years of professional software engineering experience building and operating production services.
- 3+ years of hands-on experience in at least one of: Python, Go, or Java.
- 2+ years of experience integrating ML or LLM capabilities into applications (e.g., via OpenAI, Anthropic, or open-source frameworks such as LangChain or LlamaIndex) and shipping them to production.
- Practical experience with cloud platforms (AWS or GCP), containers (Docker), and orchestration (Kubernetes).
- Proficiency with SQL and data modeling; experience building or maintaining data pipelines (e.g., Airflow, Dagster, or similar).
- Experience owning services end-to-end, including CI/CD, automated testing, observability (logging, metrics, tracing), and participation in an on-call rotation.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Preferred Qualifications
- Experience adapting or fine-tuning foundation models and implementing retrieval-augmented generation with vector databases (e.g., Pinecone, Weaviate, FAISS, or Elasticsearch with vector search).
- Track record of building internal developer tools or platforms adopted by 100+ engineers.
- Experience measuring developer productivity (e.g., DORA/SPACE), instrumenting product analytics, and running A/B or multivariate experiments.
- Knowledge of AI safety, privacy, and compliance practices (e.g., PII redaction, guardrails, model/content moderation, data residency considerations).
- Experience with event-driven systems and microservices (e.g., Kafka, Pub/Sub) and designing resilient distributed systems.
- Ability to build lightweight front-ends for internal tools (e.g., React, TypeScript) to accelerate adoption and feedback loops.
- Demonstrated mentorship and technical leadership within cross-functional teams.
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