Head of Engineering at AgencyAnalytics empowering marketing agencies with cutting - edge reporting tools. Leading engineering operations and fostering an AI - first culture in a high - trust environment.
About the role
- Engineering Manager leading catalog enrichment teams at Instacart. Focusing on building AI-native platforms for product attribute management.
Responsibilities
- Lead, mentor, and grow a team of engineers who build the platform, pipelines, and interfaces that power catalog enrichment and ML access to catalog data.
- Define and execute the technical roadmap, balancing new platform investments with reliability, observability, and developer experience for a growing user base.
- Build and operate an AI-native enrichment platform that blends LLMs, classical ML, rules, workflow orchestration, and human review into pipelines non-engineers can configure and run.
- Drive the evolution toward autonomous pipeline construction, where users express goals in plain language and the system assembles, evaluates, and optimizes workflows.
- Own the ML-facing catalog data layer, including canonical product metadata and the policy controls that separate internal model inputs from customer-facing use cases.
- Partner with ML, search, ads, commerce, and retailer teams to streamline data flows end to end and remove integration friction.
- Advocate for clear, human-readable controls for source prioritization, rights management, licensing, and compliance to ensure auditable governance.
- Boost developer and operator productivity via AI-assisted integration testing, investigation tooling, and on-call automation; set and meet SLAs on core attributes and model usage.
- Contribute hands-on to architecture discussions, design reviews, and code reviews, especially in new or exploratory areas.
Requirements
- 7+ years of software engineering experience, including 2+ years managing engineers as a people leader.
- Experience leading teams that build and operate production data or ML platforms, including both batch and streaming components.
- Strong foundation in distributed systems, data pipelines, and workflow orchestration, with demonstrated build/buy/partner decision-making.
- Ownership of data quality, coverage, or compliance commitments, with examples of frameworks and processes used to meet them.
- Excellent written and verbal communication skills, including the ability to translate complex technical work for diverse audiences.
- Experience with catalog, commerce, or product data platforms operating at large scale.
- Hands-on experience with workflow orchestration systems (e.g., Temporal, Airflow, Flink) and running them in production.
- Experience shipping applied AI/ML features in production and understanding trade-offs across LLMs, classical ML, deterministic rules, and human review.
- Proven success partnering across ML, product, and operations to deliver outcomes that require alignment and shared goals.
- Familiarity with data governance, rights management, and licensing controls in multi-stakeholder environments.
- Experience building pipeline builders, low-code/no-code tooling, or internal platforms used by non-engineers.
- Background in developer productivity tooling, including AI-assisted testing and investigation workflows.
- Success operating in fast-growing environments where both the platform and team are evolving.
Benefits
- Highly market-competitive compensation
- New hire equity grant
- Annual refresh grants
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