Forward Deployed Engineer, Audio

Responsibilities

Build the Technical Foundation for Audio

• Develop and own solutions that turn raw audio, often with unstructured or missing metadata, into organized, ready-to-sell datasets.
• Build prototypes and evolve them into reliable production systems that others can understand and operate.
• Characterize large, unfamiliar audio datasets and determine whether they support customer use cases.

Own Customer Engagements End to End

• Partner with audio leadership, technical teams, and commercial stakeholders from feasibility through post-delivery support.
• Translate customer model-development goals into executable technical plans with clear acceptance criteria.
• Own implementation and operation of customer engagements.

Turn Deal Work Into Product Leverage

• Identify platform improvements based on customer requests and field learnings.
• Identify recurring patterns that should become shared cross-vertical platform capabilities and help design and build them.
• Create audio technical playbooks and quality standards.

30-Day Goals

• Learn the platform, audio data landscape, customer and partner portfolio, and processing and delivery systems.
• Pair with an engineer on an existing audio deal.
• Identify tooling and operating-model gaps and propose a prioritized improvement plan.

60-Day Goals

• Operate an active audio deal as the primary FDE.
• Build or meaningfully extend a tool or workflow based on a customer request.
• Establish communication with FDEs and product teams to generalize deal learnings.

90-Day Goals

• Serve as the default technical owner across active audio engagements.
• Own architecture and delivery for audio customers, including post-delivery support and iteration.
• Establish an audio FDE playbook and reusable toolkit.
• Maintain a roadmap of platform investments to increase delivery capacity.

Requirements

• 3+ years of engineering experience, including meaningful exposure to customers or external technical stakeholders.
• Experience working directly with media data; audio experience is preferred.
• Experience building and operating systems that process, analyze, or deliver data at scale.
• Customer-facing ability, including translating ambiguous requirements, communicating trade-offs, and building trust with technical stakeholders.
• Demonstrated end-to-end ownership from problem definition through implementation, validation, and support.
• High ambiguity tolerance, bias to action, and sound judgment about when to investigate or push back.
• Comfort working in a fast-moving environment with concurrent priorities and time-sensitive customer work.

Nice to Have

• Early-stage company, founding-engineer, early-engineer, or startup-like experience with broad ownership.
• Hands-on Python experience.
• Product engineering experience or a strong user-focused product mindset.
• Experience with search, vector embeddings, semantic retrieval, or ML-assisted data curation.
• Experience with AWS, Dagster, Databricks, or Vercel.
• Experience with audio processing, speech or music machine learning, transcription, diarization, annotation, quality measurement, privacy, or redaction workflows.