Natera

Forward Deployed AI Solutions Engineer

Natera$105K — $132K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years experience with AI, automation, or solutions engineering.
  • Hands-on technical fluency with tools like CLIs, APIs, SQL, and Python.
  • Familiarity with large language models and agent behavior concepts.
  • Strong judgment on technical processes and outcomes.
  • Experience in regulated environments is a plus.

Responsibilities

  • Map existing and potential workflows within a specific business domain.
  • Identify opportunities where AI or automation can significantly enhance processes.
  • Quantify the potential impact of proposed changes and align with domain leadership.
  • Design end-to-end workflows highlighting agent and human responsibilities.
  • Integrate AI agents with business systems, ensuring compliance with IT standards.
  • Track and optimize agent performance using relevant KPIs and observability tools.
  • Iterate on workflows based on performance feedback and operational needs.

Benefits

  • Work within a dynamic team focused on innovation and efficiency.
  • Opportunity to directly impact business performance with measurable outcomes.
  • Access to advanced AI tools and platforms for hands-on work.
  • Engagement with domain leadership for early planning involvement.
Full Job Description
About the role

The Forward Deployed Solutions Engineer will work directly within a business domain (e.g., Commercial, Clinical Operations, Lab Operations, Sales & Marketing, Customer Experience etc.). In your role, you'll find opportunities for enhancing efficiency and productivity by looking for workflows which can be executed 10-100x faster or more often than a human team could using AI agents, integrations and other patterns. You will build, deploy, and run them in production.

You report into the central AI & Automation team, partner directly with domain leadership on priorities, and bring patterns back so the whole company compounds.
Find the leverage in your domain
  • Map the workflows in your domain - the ones running today, and the ones that don't exist yet because they weren't feasible without agents or automation tools.
  • Identify the step-change opportunities: where AI, ML, or automation unlock throughput, coverage, or speed.
  • Build the business case, quantify projected impact, and align with domain leadership on priorities.
Design the future-state workflow
  • Map structured and unstructured data flows across the systems involved (CRM, ERP, ticketing, document stores, internal tools, external SaaS).
  • Define the target workflow: what the agent does, what the human does, and where they hand off.
  • Figure out what context the agent or model needs to do the work well - and how to get it there reliably (retrieval, grounding, tool access, memory).
  • Design human-in-the-loop checkpoints so review adds value without becoming the bottleneck.
Build and connect the systems
  • Stand up agents and automation pipelines using the organization's approved AI platforms and frameworks.
  • Connect agents to business systems - via MCP servers, APIs, webhooks, CLIs, and skills - within the guardrails set by IT and security.
  • Configure tools, prompts, context, and retrieval pipelines so agents perform reliably on real work, not just in demos.
  • Handle integration gnarliness: auth, schema drift, rate limits, data quality, and the messy last-mile of enterprise systems.
  • Enable access and training for business to run the workflows
Run agents and automation pipelines in production
  • Own agent performance end-to-end. Track the KPIs that matter - throughput, quality, cost, human intervention rate, cycle time, adoption.
  • Build and manage evals. Re-run them on any material model, data, or workflow change before it ships.
  • Triage failures, tune prompts and context, iterate on the workflow, and retire agents when they're no longer the right tool.
  • Instrument observability: tracing, structured logs, dashboards. You don't ship what you can't see.
What we're looking for
  • Hands-on technical fluency. CLIs, APIs, webhooks, SQL, and Python scripting. Working knowledge of LLM and agent behavior - prompting, context, tool use, RAG, MCP, evals, failure modes. Be very comfortable with a cloud platform.
  • Trustworthy with elevated access. Least-privilege, auditability, and safe rollbacks are second nature.
  • Strong technical and process judgment. You think in outcomes and KPIs, can defend prioritization calls, and are comfortable being the most technical person in a business meeting and the most business-savvy in a technical one.
Nice to have
  • Prior experience working hand in hand with businesses to deliver measurable outcomes.
  • Hands-on experience with an enterprise agentic platform (CrewAI, LangChain, AWS Bedrock, Claude, Codex) or building directly against a model API.
  • Background in product management, solutions engineering, consulting, forward-deployed engineering, or technical operations.
  • Experience in regulated environments (HIPAA, SOC 2, GxP, SOX).
Success in year one
  • Shipped three or more workflows into production that are measurably moving a business KPI, with agent evals and observability in place.
  • Domain leadership brings you into planning early, not late.
  • Contributed at least one reusable asset another engineer on the team is now using.
  • Enabling non builders to become builders using the artifacts you created.
Compensation Ranges:

The base salary range for standard cost of living areas is: $105,700-$132,100

Higher cost of living areas: $116,200 - $145,300

Lower cost of living areas: $95,100-$118,900

Additional components such as bonus and equity are also included in this role.

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

$105,700-$132,100 USD

About Natera

Natera is a biotechnology company that focuses on genetic testing and diagnostics. The company's products are designed to help diagnose and treat genetic diseases, cancer, and other conditions. Natera's pipeline includes products for reproductive health, oncology, and organ transplantation. The company was founded in 2003 and is headquartered in San Carlos, California.
Learn more about Natera
Size
2,670 employees
Market Cap
$4.5 billion
Industry
Net Income
-$229.7 million
Founded
2004
5 Year Trend
+24.1%
Revenue
$391 million
NASDAQ

Similar Jobs

More Jobs at Natera

More Information Technology Jobs

Find similar Forward Deployed AI Solutions Engineer jobs: