Staff AI Platform Engineer – Agent & Retrieval Infrastructure

🕒 September 13

🇺🇸 United States – Remote

💵 $180k - $220k / year

⏰ Full Time

🔴 Lead

🏗️ Platform Engineer

👻 Ghost score 6%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bedrock Ocean Exploration

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

📦 Logistics

🔐 Security

Consulting • Logistics • Security

Bedrock Ocean Exploration is a vertically-integrated geophysical surveying and seafloor data company. They design, build, and operate Autonomous Underwater Vehicles (AUVs) optimized for nearshore geophysical surveys to provide high-resolution seafloor data needed for critical decision-making. The company focuses on delivering high-resolution geophysical survey data that meets stringent IHO standards using rapid, fleet-based, autonomous surveys, enhancing ocean data accessibility for industries including Offshore Wind, Cultural Resource Management, and Maritime Security.

📋 Description

• Design the Amazon Bedrock integration, including agent and action group configuration, backend APIs, model access, throughput, and cross-environment deployment • Own the retrieval pipeline from ingestion and chunking through embedding and storage in Amazon OpenSearch Serverless • Optimize index design, cost, and capacity • Adapt ingestion pipelines for internal knowledge, ocean data, and customer platforms • Address geospatial and large-binary dataset challenges • Implement security with Bedrock Guardrails, VPC and PrivateLink boundaries, least-privilege IAM, and audit trails • Define governance mechanisms for approval boundaries and safe autonomous agent actions • Implement LLMOps and observability for tracing, tool calls, and retrieval performance using CloudWatch and tools such as Langfuse or Phoenix • Build automated evaluation infrastructure, track results, and manage model-accuracy release gates • Provide abstraction layers, SDKs, and self-service environments for independent AI feature delivery • Manage infrastructure as code across environments • Ensure deployment safety and participate in incident reviews • Define the sequencing of internal, operational, ocean-data, and customer-facing retrieval capabilities • Collaborate with the core data transport team on retrieval and data-freshness requirements

🎯 Requirements

• 8+ years in software and infrastructure engineering • Deep production backend experience; Python or TypeScript preferred, Go acceptable • Staff-level ownership of technical direction • Hands-on experience standing up Amazon Bedrock in production, including agents, knowledge bases, guardrails, model access, throughput, and quotas • Containerized service deployment on ECS, EKS, or Lambda • Ownership of CI/CD • Practical RAG and vector search experience, including embeddings, chunking strategies, semantic search quality, and managed vector databases at production scale and cost • Experience building or substantially extending ingestion pipelines over messy, heterogeneous, unstructured sources • Strong AWS expertise: IAM, VPC networking, PrivateLink, Lambda, S3, KMS, CloudWatch, and infrastructure as code using Terraform, CDK, or CloudFormation • Production experience with LLM features or autonomous agents • Experience securing agentic systems, including tool permissions, prompt injection, exfiltration risk, sensitive data handling, and human-in-the-loop controls • Experience designing developer-facing APIs, SDKs, or platform services with an API-first mindset • Experience building and operating multi-tenant services with customer data isolation • Demonstrated staff-level technical leadership and system design judgment • Pragmatic preference for managed infrastructure • Ability to work across several functions on a small team and document systems thoroughly • Legally authorized to work in the US • Eligible to obtain a government security clearance if required

🏖️ Benefits

• Equity • Equal opportunity employer

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