[Hiring] Staff AI Platform Engineer @Bedrock Ocean Exploration

Role Description

We are looking for a Staff Platform Engineer to lead our AI architecture. This role goes beyond building agents on existing platforms; you will create the infrastructure itself, including:

• The orchestration layer
• The data and retrieval pipeline
• The security model required to work with production data

You will also build the tools and abstractions that allow our engineering team to implement AI features independently. This position combines software engineering, data engineering, and infrastructure operations. You will manage the full lifecycle of our Amazon Bedrock implementation, from initial data chunking to IAM access controls. While some of our data pipelines are already in place, they will require significant expansion, and others will need to be built from scratch.

Security is core to this role, not an afterthought. You will define the operational boundaries for agents with tool access, including:

• What they can access
• The actions they can perform autonomously
• The monitoring required to detect issues

Our roadmap prioritizes internal engineering and operational systems first, followed by our ocean and survey data products. Customer-facing retrieval is the final, high-stakes phase. You will play a key role in defining this sequence.

What You'll Do

• Architect Agent Orchestration: Design the Amazon Bedrock integration, including agent and action group configuration, backend APIs, model access, throughput, and cross-environment deployment.
• Manage Retrieval Data Plane: Own the end-to-end retrieval pipeline from ingestion and chunking to embedding and storage in Amazon OpenSearch Serverless. Focus on optimizing for index design, cost, and capacity.
• Extend Data Pipelines: Adapt ingestion pipelines for internal knowledge, ocean data, and customer platforms, addressing challenges specific to geospatial and large-binary datasets.
• Secure AI Infrastructure: Implement robust security including Bedrock Guardrails, VPC and PrivateLink network boundaries, least-privilege IAM, and audit trails to ensure data isolation.
• Define Agent Governance: Build the mechanisms to enforce approval boundaries for autonomous actions, ensuring agents are safe and monitored.
• Establish LLMOps & Observability: Implement comprehensive monitoring for tracing, tool calls, and retrieval performance, using CloudWatch and LLM-specific tools like Langfuse or Phoenix.
• Build Evaluation Frameworks: Create the infrastructure to run automated evaluations, track results, and manage release gates for model accuracy.
• Enable Engineering Productivity: Provide the team with abstraction layers, SDKs, and self-service environments that allow engineers to ship AI features independently.
• Operational Excellence: Manage the environment as code across all stages, ensuring deployment safety and participating in incident reviews.

Qualifications

• 8+ years in software and infrastructure engineering, including deep production backend experience (Python or TypeScript preferred, Go fine) and staff-level ownership of technical direction.
• Hands-on experience standing up Amazon Bedrock in production: agents, knowledge bases, guardrails, model access, and the throughput and quota decisions that come with them.
• Containerized service deployment on ECS, EKS, or Lambda, with CI/CD you have owned rather than inherited.
• Practical RAG and vector search experience: embeddings, chunking strategies, semantic search quality, and operating a managed vector database (OpenSearch Serverless, Pinecone, pgvector, or similar) at production scale and cost.
• Real data engineering: you have built or substantially extended ingestion pipelines over messy, heterogeneous, unstructured sources.
• Strong AWS ecosystem expertise: IAM roles and least privilege for machine identities, VPC networking and PrivateLink, Lambda, S3, KMS, CloudWatch, and provisioning safely through infrastructure as code (Terraform, CDK, or CloudFormation).
• Production LLM exposure: you have moved LLM features or autonomous agents past the prototype stage into environments other people depend on.
• A working point of view on securing agentic systems: scoping tool permissions, prompt injection and exfiltration risk, sensitive data handling in retrieval.
• Experience designing developer-facing APIs, SDKs, or platform services with an API-first mindset.
• Experience building and operating multi-tenant services, with isolation guarantees that hold when the data belongs to customers rather than to us.
• Demonstrated technical leadership and system design judgment at staff level.
• A pragmatic builder's bias.
• Comfort wearing several hats on a small team, and the discipline to write things down so the system runs without you.

Nice to Have

• Experience deploying LLM evaluations to measure accuracy over time.
• Involvement in AI red-teaming or the AI security community.
• Experience with GraphRAG or knowledge graphs.
• Experience running retrieval over geospatial, scientific, or large-binary datasets.
• Experience moving data across intermittent or unreliable links.
• Compliance experience such as SOC 2, or handling government or defense customer data.
• Background supporting data platforms, autonomous systems, or field operations.

Not a Fit If

• Your AI work has been prototypes and notebooks rather than systems other people depend on in production.
• You want to be a model researcher, a prompt engineer, or to spend your time fine-tuning models.
• You treat security as a gate at the end of a project rather than something designed from the start.
• You would rather self-host and build from scratch than adopt a managed service that already works.
• You want a mature platform team and a narrow, well-bounded scope.

Why This Role Matters

At Bedrock Ocean, our mission is to make the ocean transparent. We are building a source of deep ocean intelligence that grows with every mission. This role is about building the infrastructure that allows our teams and eventually our customers to directly query and learn from our findings. Security is woven into the foundation of your work, not added on later.

The base compensation for this role is expected to be $180,000- $220,000 annually plus equity. Bedrock Ocean is an equal opportunity employer.