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Senior Forward Deployed Engineer - Finance AI Enablement

Omada Health — Tracked from its greenhouse job board

Remote, USA Remote Senior+ Posted Jun 9, 2026
PythonReact NativeREST/APIsCloudBackendAI/LLM

About the role

Job Overview:

Omada has a dedicated AI Transformation & Enablement organization focused on embedding AI directly into how business functions operate. Rather than acting as a centralized innovation lab disconnected from day-to-day operations, this team deploys senior engineers directly into functions to partner with teams, understand their workflows, and build production AI systems that drive measurable business impact.

Finance is the next major deployment.

As the Sr. Forward Deployed Engineer supporting Finance, you will operate as the embedded AI engineering partner for the Finance organization — attending planning reviews, close cycles, forecasting discussions, operational reviews, and executive preparation processes to deeply understand how Finance operates today and how AI can transform it tomorrow. This is a 0→1 build with a team behind you, focused on turning ambiguous, high-value finance problems into production systems used by executives and operators every day. You will own each agent end-to-end: from discovery and prototyping, to shipping, monitoring, and iterating.

You will partner closely with the Sr. Director, Strategic Finance, who owns the Finance AI roadmap and business prioritization, while remaining part of Omada’s AI Transformation & Enablement engineering organization, where you will receive technical leadership, architecture guidance, peer collaboration, and engineering support from other Forward Deployed Engineers solving similar challenges across the company.

This role is highly cross-functional and combines elements of AI engineering, systems integration, workflow automation, product thinking, business partnership, and organizational enablement. You will design, build, deploy, monitor, and continuously improve AI-powered systems that help Finance teams operate more efficiently, improve accuracy and consistency, accelerate decision-making, and scale institutional knowledge.

The systems you build will operate within a highly regulated and compliance-sensitive environment that includes SOX, HIPAA, security, and data governance considerations. As part of the AI Transformation & Enablement organization, you will help shape the standards, governance patterns, and operational practices that define responsible enterprise AI adoption at Omada.

What You’ll Own:

Finance AI Integration & Knowledge Layer

Design and build the Finance-specific AI integration layer that connects AI systems to enterprise finance platforms, operational data, and institutional knowledge sources.

This includes:

Integrating AI systems with platforms such as NetSuite, Adaptive Planning, FloQast, AWS, and internal data warehouses

Building retrieval and knowledge systems over financial documentation, board materials, KPI definitions, investor communications, and forecasting models

Developing reusable AI workflow and orchestration patterns for Finance use cases

Enabling conversational and natural-language interaction with operational and financial data

Partnering with central Engineering and AI platform teams to adopt and extend shared AI infrastructure patterns

You will design systems that allow Finance teams to progressively own configuration, evaluation, and operational management of AI workflows over time.

AI-Powered Financial Quality & Controls

Build AI-enabled quality assurance and validation systems that improve confidence, consistency, and operational rigor across Finance workflows.

Examples include:

Metric reconciliation across reporting materials and presentations

Narrative and KPI consistency validation

Financial calculation verification

Reporting integrity and formatting validation

AI-assisted review workflows with human-in-the-loop oversight

Evaluation and auditability patterns supporting SOX-aligned processes where applicable

You will help establish evaluation frameworks and review processes that ensure AI systems are reliable, measurable, and operationally trustworthy.

Operational Intelligence & Automation

Develop AI systems that continuously analyze operational and financial processes to surface insights, anomalies, optimization opportunities, and business risks.

Areas may include:

Cost and spend monitoring

Vendor and procurement analysis

Contract and compliance monitoring

Pricing and operational trend analysis

Cloud and AI platform cost optimization

Automated summarization, alerting, and root-cause analysis

You will focus on delivering practical AI solutions that improve operational efficiency and support faster, more informed decision-making.

Market, Earnings & Strategic Intelligence

Build AI-powered intelligence capabilities that help Finance leadership monitor external market activity and prepare executive-level materials more efficiently.

Examples include:

Monitoring competitor activity, earnings calls, filings, and analyst commentary

Supporting benchmarking and market intelligence workflows

Assisting with earnings preparation, executive Q&A, and board preparation workflows

Cross-referencing and validating data across financial narratives, trend reporting, and investor-facing materials

Financial Workflow & Narrative Automation

Develop AI-enabled workflows that accelerate operational execution and reduce manual effort across recurring Finance processes.

Examples may include:

Monthly and quarterly reporting commentary

Flash reports and KPI summaries

Forecast and enrollment analysis

Revenue and operational model validation

Executive memo and board material drafting support

You will partner closely with Finance SMEs to ensure workflows remain operationally accurate, transparent, and trusted.

AI Evaluation, Enablement & Adoption

Enable Finance teams to effectively evaluate, use, and extend AI systems over time.

This includes:

Building evaluation frameworks, regression testing, and quality scorecards

Establishing operational review and feedback loops

Training Finance SMEs on AI evaluation and workflow management

Promoting transparency around AI capabilities, limitations, and reliability

Helping Finance teams grow long-term AI fluency and operational ownership

Success in this role is not just measured by systems you build, but by how effectively the organization adopts and scales them.

Cross-Functional Partnership & Operating Model:

This role operates with two closely connected partnership models by design.

From a business perspective, you will be deeply embedded within the Finance organization and aligned to Finance priorities, workflows, operational rhythms, and strategic initiatives. The Sr. Director, Strategic Finance will own roadmap prioritization and business outcomes for Finance AI initiatives.

From a technical perspective, you will remain part of Omada’s AI Transformation & Enablement engineering organization, where you will collaborate with other Forward Deployed Engineers, participate in shared architectural standards, receive technical mentorship and code review, and contribute reusable patterns that scale across other functions.

You will regularly partner across:

Finance

Accounting

IT

Security & Compliance

Data & Engineering

Business Systems

Enterprise AI & Automation teams

This role requires balancing speed, innovation, governance, operational reliability, and stakeholder alignment in a rapidly evolving AI landscape.

What Makes This Role Different:

Embedded partnership model: You work directly inside Finance while remaining part of a centralized AI engineering organization

High ownership environment: You will own initiatives from discovery through deployment and iteration

Real operational impact: The systems you build will be used daily by Finance operators and leadership teams

AI-first transformation work: This is not incremental automation — this role helps redefine how Finance workflows operate

Strong executive exposure: You will partner closely with senior leadership across Finance, Technology, IT, and Security

Builder and enabler: Success is measured not only by what you build, but by how effectively the organization adopts and scales it

Long-term growth opportunity: This role evolves from hands-on builder into strategic architect and AI transformation leader over time

Tools & Technologies:

We do not expect expertise in every tool on day one, but you should be comfortable learning and working across a modern enterprise AI ecosystem.

Examples include:

AI and orchestration frameworks

Python services and APIs

AWS and cloud-native infrastructure

Enterprise Finance platforms and operational systems

Data warehouses and analytics environments

AI evaluation and observability tooling

Workflow automation and integration platforms

Governance, access control, and enterprise AI operational tooling

What Great Looks Like:

Builds strong trusted partnerships with Finance leaders and subject matter experts

Delivers production-ready AI systems that create measurable operational impact

Balances rapid experimentation with enterprise-grade reliability and governance

Creates AI workflows that are understandable, auditable, and operationally sustainable

Enables Finance teams to independently evaluate and operate AI-assisted workflows over time

Operates effectively in ambiguity and turns loosely defined problems into scalable solutions

Communicates AI capabilities, limitations, and tradeoffs clearly to technical and non-technical audiences

Contributes reusable patterns and operational practices that scale AI adoption across the organization

Demonstrates strong judgment in compliance-sensitive environments involving financial and operational data

Embodies Omada values through collaboration, ownership, adaptability, and execution

Candidate Requirements:

AI & Software Engineering

5+ years of experience building and deploying software, data, automation, or AI-powered applications

2+ years of recent hands-on experience building LLM-based or AI-enabled systems in production environments

Strong experience designing AI workflows including retrieval systems, orchestration patterns, tool usage, evaluation frameworks, and multi-step reasoning systems

Strong proficiency in Python and experience building production-quality backend services, APIs, integrations, and automation workflows

Experience integrating enterprise systems and operational data into AI-enabled workflows

Enterprise Systems & Data

Experience working with enterprise business systems such as ERP, planning, financial, or operational platforms

Experience designing retrieval or contextual knowledge systems across large document and metric corpora

Familiarity with structured and unstructured enterprise data environments

Understanding of operational monitoring, evaluation, and observability concepts for AI systems

Partnership & Communication

Excellent communication and stakeholder management skills

Proven ability to partner directly with non-technical teams and translate business workflows into scalable technical solutions

Experience enabling business users through training, documentation, and operational coaching

Comfortable operating within highly cross-functional and rapidly evolving environments

Operating Style

Thrives in ambiguity and 0→1 environments

Strong ownership mentality with the ability to independently drive initiatives forward

Comfortable balancing embedded business partnership with centralized engineering alignment

Demonstrates strong prioritization and judgment across competing initiatives

Governance, Security & Compliance

Awareness of governance, security, and compliance considerations related to enterprise AI adoption

Familiarity working within regulated or compliance-sensitiv…

What the index says about this role

  • First seen by JobLarper — Aug 2, 2026, 6 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
  • No pay range in our index for this listing. Across 255 indexed Solutions Architect roles in US that do publish one, the middle half sits between $170k and $225k, median $200k — JobLarper's read of the market, not a figure from Omada Health.
  • What Solutions Architect roles ask for — across 1,615 indexed openings: Python (46%), REST/APIs (42%), AI/LLM (36%), Cloud (31%), ML (29%). This posting names Python, REST/APIs, AI/LLM, Cloud, React Native.
  • Omada Health is hiring actively — 17 open roles indexed.

Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.

⚡ JobLarper watched this role appear on Omada Health's official board on Jun 9, 2026. Sign up free to get alerted minutes after roles like this go live, and tailor your real résumé to the exact description — nothing invented.

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