Applied AI Engineer, Derivative Path
CA$110-150k
+ Equity + Bonus
Derivatives technology & advisory for financial institutions
Be an early applicant
Derivatives technology & advisory for financial institutions
101-200 employees
Be an early applicant
CA$110-150k
+ Equity + Bonus
101-200 employees
Company mission
To modernize risk management and financial technology.
Role
Who you are
- You are someone who moves with purpose. You form a view based on what you know, test it against reality, and adjust as you learn. Ambiguity is not a blocker for you; it is just the nature of early-stage problems
- You are hands-on by preference. Writing code, building pipelines, running experiments: that is where you do your best thinking
- You are a quick study. Financial derivatives is a specialized domain and we do not expect you to know it coming in. What we do expect is genuine curiosity, because the depth you develop here will directly shape the quality of what you build
- You stay constructive. This is a team working on consequential problems in a demanding environment. When things go sideways, you focus on the path forward. Collaboration and good energy matter
- You are pragmatic about tools and languages. You reach for whatever the project calls for and stay open to better options as they emerge
- Building with LLMs: prompt engineering, RAG, fine-tuning, agents, or inference pipelines
- Data engineering: designing and building pipelines that feed real workflows
- ML or data science work, especially in complex or data-constrained environments
- Working knowledge of Python and common AI/ML frameworks (PyTorch, HuggingFace, LangChain, or similar)
- MLOps or production AI experience: getting models out of notebooks and into the real world
- Cloud platform experience (Azure, AWS, or GCP)
- Experience with reinforcement learning or financial derivatives is a bonus, not a baseline
What the job involves
- We are looking for an Applied AI Engineer to join the AI Lab team within DerivativeEDGE
- Reporting to the AI Lab lead, you will work closely with Engineering, Product, and domain experts to design, build, and ship AI-powered features in a complex, high-stakes financial environment
- This is a hands-on engineering role
- You will move between experimentation and production, work through ambiguous problems, and deliver AI capabilities that real clients use
- Generic approaches do not get you far here
- The expectation is that you learn the domain, move with urgency, and build things that hold up
- The core of this role sits at the intersection of Generative AI, Agentic Workflows, and Data Engineering: building LLM-powered solutions, designing agents that can reason and act across complex workflows, and making sure the right data is available to support it all
- Applied to financial derivatives, these are genuinely hard problems worth solving
- Build and ship LLM-powered features across the DerivativeEDGE platform, working directly with domain experts to translate complex financial workflows into reliable AI capabilities
- Design and implement agentic workflows that can reason, act, and recover gracefully across multi-step processes in a production environment
- Own the data engineering layer that feeds AI systems: pipelines, retrieval architectures, context design, and data quality
- Move fluidly between experimentation and production. You will prototype quickly, evaluate honestly, and know when something is ready to ship
- Contribute to the AI Lab's broader technical direction, including evaluations, tooling, MLOps practices, and the patterns the team builds on
- Depending on where projects take you, work may also touch NLP, model fine-tuning, synthetic data, or reinforcement learning. Curiosity and a willingness to build in new areas are expected
Our take
Derivative trading often proves unattainable for many organizations due to barriers like limited access, complex compliance regulations, and intricate hedge accounting procedures. Derivative Path effectively addresses these challenges through its capital markets platform.
A key strength of Derivative Path lies in the collective expertise of its team, comprising seasoned professionals with backgrounds in private equity and venture capital from reputable institutions like Wells Fargo and Barclays. Leveraging this hands-on experience, the company adeptly meets the needs of financial institutions and trading firms. Providing institutions with a more efficient avenue for accessing capital markets, earning the company an impressive client roster that includes Simmons Bank and United Community Bank.
In the rapidly evolving landscape of capital markets technology, companies like AlphaSense vie for prominence. However, Derivative Path distinguishes itself by its dedicated focus on derivatives and an array of tools, differentiating itself from other trading fintechs primarily centred on data analysis.
Steph
Company Specialist at Welcome to the Jungle
Insights
35% employee growth in 12 months
Company
Funding (1 round)
Jun 2020
$35m
GROWTH EQUITY VC
Total funding: $35m
Company HQ
Walnut Creek, CA
Leadership
Pradeep Bhatia
(Co-Founder & CEO)Pradeep began their career as an Investment Banking Associate at US Bank, before joining Societe Generale as VP of Leveraged Finance. Prior to co-founding Derivative Path in 2013, they were the Head of Bank Coverage at Wells Fargo Bank.
John Fleming
(Co-Founder & COO)After co-founding Derivative Path in 2013, John served as the CTO until 2021, when they moved into the role of COO. Previously, they were a Managing Director at Wells Fargo, a Product Manager at Calypso Technology and Integral Development Corp, and a VP at Societe Generale.
Zack Nagelberg
(Co-Founder & President)After co-founding Derivative Path in 2013, Zack served as the Head of Business Development until 2021, when they moved into the role of CGO until 2026. Previously, they were an Analyst/Associate at Wells Fargo Securities.
Frank Purnell
(Co-Founder & CIO)After co-founding Derivative Path in 2013, Frank served as the Head of Product Management until 2021, when they moved into the role of CPO until 2023, and then into the role of CIO. Previously, they spent over 7 years at Wells Fargo as an IT Proejct Manager, Commodities Trader/Developer and Trading Manager.
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