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Agentic Engineer
$160k – $200k base
6
Denver, CO
About the Role
Want to be at the frontier of how the products of tomorrow get built? We're hiring an Agentic Engineer who builds by directing AI coding agents, and owns the outcome.
Straddle is building the rails for the next era of payments, with the goal of moving money as fast as data moves. You'll help build that platform a level up from traditional coding: turning ambiguous problems into precise specs, breaking them into agent-sized tasks, running several coding agents in parallel, and reviewing what they ship with a high bar. You'll write code by hand when that's the faster path, and delegate the rest. Because this is the infrastructure money runs on, security and correctness are never optional, and the bar you hold on agent output is what keeps it that way. You'll also help shape how Straddle builds with agents: the standards and tooling the rest of engineering will run on.
Key Responsibilities
Spec before you build. Turn product and technical intent into precise specs agents can execute: clear interfaces, scope, and acceptance criteria. This is the highest-leverage part of the job.
Decompose for agents. Break features, migrations, and bugs into agent-sized tasks. Knowing what's too big for one pass, and how to slice it, is the craft.
Direct and orchestrate. Run multiple agents in parallel across features, integrations, and backlog. Keep them unblocked, correct course early, reset when a session drifts.
Own verification. Build the tests, builds, and checks that let agents self-correct. On payment and compliance paths, if you can't verify it, it doesn't ship.
Review at volume. Read agent diffs critically for correctness, security, performance, and fit. You own the merge, the deploy, and the consequences.
Improve the system. Maintain the shared context agents rely on (project memory, skills, hooks, integrations, CI) so everyone's agents get better. Treat specs and agent config as version-controlled engineering.
Security and compliance. Apply security best practices to agent-generated code: authn/authz, encryption, common-vulnerability defense, and fintech controls (PCI, SOC 2).
Set the standard. Establish conventions and coach the team on specification, verification, and reviewing code they didn't write by hand.
Required Qualifications
Strong engineering fundamentals. 5+ years building production software in a modern language, with the judgment to tell solid design from fragile design. That judgment is what makes directing and reviewing agents effective.
Hands-on agentic experience. You've shipped real work with tools like Claude Code or Cursor agent mode, well beyond autocomplete.
Specification and decomposition. You break down hard problems and write them down precisely.
Verification mindset. Fluent in testing strategy and making correctness machine-checkable, with sharp debugging and root-cause skills.
High-rigor review. You review fast and well, including code you didn't author, without dropping the bar.
At home with non-determinism. You evaluate output quality instead of assuming it.
Communication and teamwork. Strong writer, collaborates well with product, design, and data science.
Preferred Qualifications
Computer science foundations. A real understanding of CS fundamentals (data structures, algorithms, complexity). No specific degree required.
Fintech or payments. Payment processing, banking software, ledgers, ACH, or software compliance.
Agent tooling or evals. You've built internal tooling, eval harnesses, prompts, skills, or CI that made a team better with AI.
Our stack. Less important than your judgment, as long as you're comfortable reviewing it as agent output: .NET (C#), TypeScript, and PostgreSQL, with solid architecture instincts (CQRS, Clean Architecture, DDD, SOLID).
Cloud. AWS, GCP, or Azure, architected for scale and reliability.
Leadership. You've led projects or helped a team adopt a new way of working.
Apply now
Your application will be reviewed by us. We'll get back to you quickly. We can't wait to meet you!
About the job
Job type
Full-Time, Hybrid
Salary
$160k – $200k base
Benefit you’ll get
Flexible Work Environment – We offer hybrid and remote options so you can work where you’re most productive, whether that’s at home, in-office, or a mix of both.
Equity Ownership – As an early team member, you’ll receive equity in the form of options or RSUs; your contributions grow the company, and you share in the upside.
Unlimited PTO – Take the time you need to rest, recharge, or handle life outside of work. We trust our team to balance time off with results.
Health & Wellness Coverage – Comprehensive medical, dental, and vision plans help keep you and your family healthy, with 100% employee premium coverage on select plans.
Paid Parental Leave – We support growing families with fully paid time off for new parents, including adoption and foster care.
Professional Development – We invest in your growth with paid courses, certifications, and conference opportunities tailored to your role and interests.
Home Office & Equipment Stipend – Receive a stipend to set up your home workspace and get the tools you need to work comfortably and effectively.
Team Retreats – We host regular offsites to align on strategy, collaborate face-to-face, and have fun as a team.
Autonomy & Ownership – We give you space to lead initiatives, own outcomes, and shape the direction of your work without micromanagement.
Mission-Driven Work – Help build infrastructure that moves money more efficiently, securely, and transparently for modern businesses.
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Company Overview
Straddle is building the intelligence layer for modern payments, enabling smarter, faster, and more reliable financial decisions through data and machine learning. We operate at the intersection of fintech, data infrastructure, and real-time decisioning, where the models and insights we build directly impact transaction success, fraud prevention, and customer experience.
We are a fast-moving, high-ownership team that values speed, clarity, and pragmatic execution. We believe in delivering impact quickly, iterating continuously, and building systems that scale as the business grows.
Position Overview
We are seeking a Senior Data Science Product Manager to drive the discovery, scoping, and cross-functional orchestration of Straddle's data and ML-powered product capabilities.
This role bridges the gap between data science, product, and the market. You will work closely with product leadership to understand Straddle's product roadmap, identify where data and ML can create differentiated value, and translate those opportunities into well-scoped, high-impact data product initiatives. Examples include intelligent routing systems that maximize bank connection success across providers, balance prediction models that reduce payment failures and unlock new product offerings like guaranteed payments, and risk scoring features that shape how payment products are priced and rolled out.
Today, data product strategy and roadmap ownership sits with the Head of Data Science. As the team scales, this role will serve as the connective tissue between the data science team and the rest of the organization, engaging directly with customers, attending industry events, understanding the payments landscape, and channeling market needs back into the data product roadmap. You will drive discovery, scoping, and cross-functional coordination for data initiatives, and be a strong voice contributing to leadership's Data Roadmap and OKRs.
The ideal candidate is someone who thinks like a product manager but speaks the language of data science. Comfortable scoping an ML feature, challenging a model's assumptions, and presenting a data product strategy to leadership in the same week.
Essential Functions
Drive discovery, scoping, and cross-functional coordination for data science and ML initiatives that support Straddle's core payment products. Surface opportunities, write proposals, and keep projects on track in partnership with the Head of Data Science
Partner with product leadership to understand the full product landscape and identify where data-driven capabilities (models, features, scoring, intelligence) can create competitive advantage
Translate product and business needs into well-defined data science project briefs, including problem framing, success metrics, data requirements, and delivery milestones
Engage directly with customers, prospects, and partners to understand real-world payment challenges and surface opportunities for data products
Represent Straddle's data capabilities externally at industry events, fintech meetups, and partner conversations. Bring market intelligence back to the team
Collaborate with data science and engineering to ensure data products are built with the right trade-offs between speed, accuracy, and scalability
Identify data gaps where acquiring new data sources, improving data quality, or connecting to new providers can meaningfully improve product and model outcomes
Define and track success metrics for data products post-launch, driving iteration based on real-world performance
Manage intake and triage of cross-functional data requests, providing recommendations on prioritization to the Head of Data Science
Build and maintain PRDs and product proposals for data science initiatives, ensuring alignment across product, engineering, and leadership
Desired Experience & Skills
5+ years in product management, data science, or a hybrid data product role
Strong understanding of machine learning concepts. You don't need to build models, but you need to know what's feasible, what's hard, and what questions to ask
Demonstrated experience translating business problems into data/ML product requirements
Track record of shipping data-powered features or products in a B2B or fintech context
Strong product intuition. You understand user needs, market dynamics, and how to prioritize ruthlessly
Experience working directly with customers or in customer-facing contexts (sales engineering, solutions, product discovery)
Familiarity with payments, open banking, risk/fraud, or financial services is strongly preferred
Excellent communication skills. You can write a clear PRD, run a stakeholder review, and present to leadership with equal comfort
Comfort operating in ambiguity. You thrive when the problem isn't fully defined yet
Experience with data platforms (Databricks, SQL, analytics tools) is a plus
Technical Familiarity
Machine learning product lifecycle: problem framing, feature design, model evaluation, deployment, monitoring
Data infrastructure concepts: pipelines, feature stores, lakehouse architecture, data quality
Payment systems: ACH, RTP, open banking, identity verification, risk scoring
A/B testing and experimentation design
Analytics and BI tools (dashboards, cohort analysis, funnel metrics)
Familiarity with Linear, Notion, or similar product management tooling
Culture Fit
Speed over perfection — momentum creates opportunity; we deliver, iterate, and improve
Ownership mentality — we don't stop at "our part"; we ensure outcomes
Honest, data-driven thinking — we trust the data, even when it's inconvenient
Curiosity and creativity — we ask "why," explore ideas, and challenge assumptions
Pragmatic execution — we balance long-term scalability with immediate business impact
Collaborative mindset — we think out loud, share context, and make each other better
We are building systems that directly impact real financial outcomes. That responsibility demands high standards, strong judgment, and a bias toward action.
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Senior Product Data Scientist
We are seeking a Data Science Product Manager to report into the data science function, driving the strategy and execution behind models that detect fraud, optimize payment routing, and surface actionable insights for our clients. You will work closely with data and engineering teams to ensure data products move from discovery to production with speed and clarity.
$150k – $190k base
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Company Overview
Straddle is building the intelligence layer for modern payments, enabling smarter, faster, and more reliable financial decisions through data and machine learning. We operate at the intersection of fintech, data infrastructure, and real-time decisioning, where the models and insights we build directly impact transaction success, fraud prevention, and customer experience.
We are a fast-moving, high-ownership team that values speed, clarity, and pragmatic execution. We believe in delivering impact quickly, iterating continuously, and building systems that scale as the business grows.
Position Overview
We are seeking a Senior Data Science Product Manager to drive the discovery, scoping, and cross-functional orchestration of Straddle's data and ML-powered product capabilities.
This role bridges the gap between data science, product, and the market. You will work closely with product leadership to understand Straddle's product roadmap, identify where data and ML can create differentiated value, and translate those opportunities into well-scoped, high-impact data product initiatives. Examples include intelligent routing systems that maximize bank connection success across providers, balance prediction models that reduce payment failures and unlock new product offerings like guaranteed payments, and risk scoring features that shape how payment products are priced and rolled out.
Today, data product strategy and roadmap ownership sits with the Head of Data Science. As the team scales, this role will serve as the connective tissue between the data science team and the rest of the organization, engaging directly with customers, attending industry events, understanding the payments landscape, and channeling market needs back into the data product roadmap. You will drive discovery, scoping, and cross-functional coordination for data initiatives, and be a strong voice contributing to leadership's Data Roadmap and OKRs.
The ideal candidate is someone who thinks like a product manager but speaks the language of data science. Comfortable scoping an ML feature, challenging a model's assumptions, and presenting a data product strategy to leadership in the same week.
Essential Functions
Drive discovery, scoping, and cross-functional coordination for data science and ML initiatives that support Straddle's core payment products. Surface opportunities, write proposals, and keep projects on track in partnership with the Head of Data Science
Partner with product leadership to understand the full product landscape and identify where data-driven capabilities (models, features, scoring, intelligence) can create competitive advantage
Translate product and business needs into well-defined data science project briefs, including problem framing, success metrics, data requirements, and delivery milestones
Engage directly with customers, prospects, and partners to understand real-world payment challenges and surface opportunities for data products
Represent Straddle's data capabilities externally at industry events, fintech meetups, and partner conversations. Bring market intelligence back to the team
Collaborate with data science and engineering to ensure data products are built with the right trade-offs between speed, accuracy, and scalability
Identify data gaps where acquiring new data sources, improving data quality, or connecting to new providers can meaningfully improve product and model outcomes
Define and track success metrics for data products post-launch, driving iteration based on real-world performance
Manage intake and triage of cross-functional data requests, providing recommendations on prioritization to the Head of Data Science
Build and maintain PRDs and product proposals for data science initiatives, ensuring alignment across product, engineering, and leadership
Desired Experience & Skills
5+ years in product management, data science, or a hybrid data product role
Strong understanding of machine learning concepts. You don't need to build models, but you need to know what's feasible, what's hard, and what questions to ask
Demonstrated experience translating business problems into data/ML product requirements
Track record of shipping data-powered features or products in a B2B or fintech context
Strong product intuition. You understand user needs, market dynamics, and how to prioritize ruthlessly
Experience working directly with customers or in customer-facing contexts (sales engineering, solutions, product discovery)
Familiarity with payments, open banking, risk/fraud, or financial services is strongly preferred
Excellent communication skills. You can write a clear PRD, run a stakeholder review, and present to leadership with equal comfort
Comfort operating in ambiguity. You thrive when the problem isn't fully defined yet
Experience with data platforms (Databricks, SQL, analytics tools) is a plus
Technical Familiarity
Machine learning product lifecycle: problem framing, feature design, model evaluation, deployment, monitoring
Data infrastructure concepts: pipelines, feature stores, lakehouse architecture, data quality
Payment systems: ACH, RTP, open banking, identity verification, risk scoring
A/B testing and experimentation design
Analytics and BI tools (dashboards, cohort analysis, funnel metrics)
Familiarity with Linear, Notion, or similar product management tooling
Culture Fit
Speed over perfection — momentum creates opportunity; we deliver, iterate, and improve
Ownership mentality — we don't stop at "our part"; we ensure outcomes
Honest, data-driven thinking — we trust the data, even when it's inconvenient
Curiosity and creativity — we ask "why," explore ideas, and challenge assumptions
Pragmatic execution — we balance long-term scalability with immediate business impact
Collaborative mindset — we think out loud, share context, and make each other better
We are building systems that directly impact real financial outcomes. That responsibility demands high standards, strong judgment, and a bias toward action.