Staff Forward Deployed AI Solutions Engineer

Role Description

The Staff 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.

• 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.

Qualifications

• 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.
• Comfortable being the most technical person in a business meeting and the most business-savvy in a technical one.

Requirements

• 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: $152,100-$190,100.
• Higher cost of living areas: $167,300 - $209,100.
• Lower cost of living areas: $136,900-$171,100.
• 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.

Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents.
• Free testing for Natera employees and their immediate families in addition to fertility care benefits.
• Pregnancy and baby bonding leave.
• 401k benefits.
• Commuter benefits.
• A generous employee referral program.

Company Description

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.