Role Overview

The Enterprise AI Platform Engineer is responsible for build and delivery of Natera’s enterprise agentic AI platform. The enterprise AI platform will be used to prototype and build multiple agentic AI solutions using low code across Natera in a federated approach.This is a hands-on technical leadership role at the intersection of engineering excellence, low code platform design, and applied GenAI engineering.

You will architect and build the core AI operating system that powers modular, low-code enterprise AI agentic automation that is complete with agent templates, agent orchestration engine, data and MCP connectors, prompt optimization capabilities, evaluation guardrails, abstracted AI services, intelligent data extraction and reasoning capabilities. The platform empowers citizen developers, business analysts, and engineers to prototype and test AI-powered workflows using a low-code interface, while enabling developers to extend functionality through a pro-code framework.

Key Responsibilities

Platform Architecture & Core Infrastructure

Design: Design and implement the core architecture of the Enterprise AI Platform — low code, modular, scalable, and secure.
Agentic Orchestration: Build the agent orchestration runtime, including task queues, state management, and inter-agent communication.
Complexity: Architect for long-running, resilient AI workflows, enabling agents to execute and monitor multi-step, asynchronous processes.
Low code abstraction: Develop APIs and services for automation, evaluation, and agent lifecycle management.
Deployment: Establish DevOps, CI/CD pipelines, and configuration management to ensure smooth deployment at scale.

Low-Code/Pro-Code Experience

Low-Code Interface: Build an intuitive visual builder that allows business users to compose agent workflows through drag-and-drop and configuration.
Pro-Code Mode: Provide a developer extension layer where engineers can author and deploy agents in code (Python, TypeScript) directly into the same framework.
Unified Runtime: Ensure both low-code and pro-code workflows share common infrastructure for orchestration, evaluation, and governance.
Transparency & Debugging: Surface workflow traces, model evaluations, and output explanations directly in the user interface.
Experimentation & Versioning: Support iterative experimentation, evaluation-based comparison, and rollback through integrated version control.

Agentic Orchestration & Long-Running Agents

Orchestration Engine: Build a robust orchestration system supporting both short-lived agent calls and long-running AI agents that persist over time to automate complex processes.
Workflow Automation: Enable orchestration of multiple agents with shared state, scheduling, dependency resolution, and event-driven execution.
Enterprise Integration: Connect agents to core enterprise systems to perform real-world actions securely.
Autonomy & Resilience: Implement mechanisms for persistence, checkpointing, recovery, and human-in-the-loop interventions.
Human in the Loop Feedback: Design human-in-the-loop and self-assessment mechanisms for continuous prompt and workflow improvement.
Evaluation as a Core Layer: Architect an evaluation-first framework for monitoring and improving AI agent performance across all workflows.

AI Services & Capabilities

MCP Integration: Integrate with Model Context Protocols (MCPs) to enable plug-and-play connectivity with external systems and actions.
Retrieval-Augmented Generation (RAG): Build services to retrieve information from unstructured data using vector databases and retrieval pipelines.
Prompt Optimization & Evaluation: Implement automated systems for prompt tuning, evaluation, and feedback loops to ensure reliable results.
Abstracted AI Services: Build modular APIs for AI services such as unstructured document processing, information retrieval, information summarization, data extraction, content generation, classification etc.
Evaluation as a Core Layer: Architect an evaluation-first framework for monitoring and improving AI agent performance across all workflows.
Reusable Components: Create shared, composable AI primitives (e.g., document loaders, semantic routers, extractors) to accelerate workflow design.

Governance, Security & Observability

Enforce governance, security, and compliance principles (SOC2, HIPAA, GDPR) across all platform operations.
Implement RBAC, audit logging, and lineage tracking for all data and agent interactions.
Build observability tools for tracing, cost monitoring, and system performance metrics.
Integrate evaluation-based guardrails that detect hallucinations, bias, or policy violations in real time.
Metric Tracking: Create structured metrics dashboards (precision, recall, task success rate, cost efficiency) for every deployed agent.

Technical Leadership & Collaboration

Establish technical standards, documentation, and engineering patterns for future platform development.
Collaborate with business stakeholders, data scientists, and product teams to identify automation use cases and measure ROI via evaluation metrics.
Mentor future engineers and contribute to an engineering culture centered on safety, transparency, and impact.
Continuously explore emerging agent frameworks, vector stores, and evaluation methodologies.

Qualifications

Required

12+ years of software engineering experience, with 8+ years in platform or distributed systems architecture.
Proven expertise in implementing workflow orchestration or automation systems
Proficiency in Python with deep experience in backend architecture and API design.
Experience with low-code/no-code automation platforms (Zapier, n8n etc.), internal developer platforms (IDPs), or workflow engines (Temporal, Airflow).
Experience in working with well known agentic cloud platforms (e.g. AWS Bedrock agents, AgentCore etc.).
Hands-on experience with LLMs, RAG, vector databases, and orchestration frameworks (LangChain, LlamaIndex, AutoGen, DSPy).
Fluency in cloud infrastructure, Kubernetes, Docker, and CI/CD automation.
Knowledge of observability and telemetry systems for event-driven environments.
Familiarity with AI governance and evaluation frameworks, LLM safety, drift detection, bias detection, hallucination, explainability, and compliance (e.g., HIPAA, CLIA, FDA).

Preferred:

Advanced degree (MS/PhD) in Computer Science, AI/ML, engineering or related field.
Experience in healthcare, pharma, diagnostics, or other regulated industries.

The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

Remote USA

$174,400—$218,000 USD

OUR OPPORTUNITY

Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.

The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.

WHAT WE OFFER

Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!

For more information, visit www.natera.com.

Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.

All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws.

If you are based in California, we encourage you to read this important information for California residents.

Link: https://www.natera.com/notice-of-data-collection-california-residents/

Please be advised that Natera will reach out to candidates with a @natera.com email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.

For more information:
- BBB announcement on job scams
- FBI Cyber Crime resource page