Senior Forward Deployed Engineer - Finance AI Enablement
Omada Health · United States · 2 wk ago
RemoteRemoteEngineering$143k–$178k/yrFull-time
About the role
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.
Responsibilities
Finance AI Integration & Knowledge Layer
- 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
AI-Powered Financial Quality & Controls
- Building 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, and evaluation and auditability patterns supporting SOX-aligned processes where applicable
Operational Intelligence & Automation
- Developing 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
Market, Earnings & Strategic Intelligence
- Building 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, and cross-referencing and validating data across financial narratives, trend reporting, and investor-facing materials
Financial Workflow & Narrative Automation
- Developing 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
AI Evaluation, Enablement & Adoption
- 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
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-sensitive environments involving financial, operational, or healthcare-related data
- Comfortable incorporating human review, evaluation, and auditability into AI workflows
Qualifications
- BS/MS in Computer Science, Engineering, or a related field
- Experience with relevant tools and technologies as listed in the Tools & Technologies section
- Passion for using AI to solve complex business problems
- Ability to work independently and as part of a team
- Strong problem-solving and analytical skills
- Ability to communicate complex technical ideas to non-technical stakeholders