Senior AI Forward Deployed Engineer

About the job

The Wissen team continues to expand its footprint in the USA, Canada, UK, Australia, and India. More openings to come as we continue to grow the team!

Please read below for a brilliant career opportunity.

Role: Senior Forward Deployed Engineer, AI Enablement

Title: AVP/VP

Location: NYC, NY or NJ

Mode of Work: 3 days/week onsite required

Required Experience: 7- 10 years

Role Overview

• Wissen Technology works with banks, asset managers, broker dealers and market infrastructure firms on the systems that run their businesses. Our clients are now asking a harder question than “which model should we use.” They want to know how to get an AI system into production, inside their control environment, delivering a measurable result that a business owner will sign off on.
• The Forward Deployed Engineer is the person who answers that question by building it. You will embed with a client team, usually one or two accounts at a time, and take a use case from a whiteboard conversation to a working system that runs on the client’s infrastructure and passes the client’s governance review. You write production code. You also sit in the meeting where the head of operations explains why the last three automation projects stalled, and you figure out what to do differently.

What you will do

• Lead technical discovery with client business and technology stakeholders. Identify the underlying process problem, define what success looks like in numbers, and scope a first release that can be delivered in weeks rather than quarters.
• Design and build production AI applications on the client’s stack: LLM-backed services, agent workflows with tool use, retrieval pipelines over structured and unstructured enterprise data, and the integrations that connect them to existing systems of record.
• Own the solution end to end, from proof of value through hardening, deployment, monitoring and handover. When something breaks in production, you are the first call.
• Build evaluation frameworks that a model risk or compliance function will accept: offline test sets, hallucination and accuracy checks, regression suites, human review workflows, and the documentation that goes with them.
• Work across model providers and cloud platforms as client mandates require. Most of our clients run on Azure or AWS with a mix of OpenAI, Anthropic and open weight models behind Bedrock or Azure AI, and you should be comfortable moving between them.
• Navigate enterprise constraints as part of the job rather than as an obstacle to it: information security review, data residency, entitlements, change management, vendor onboarding and audit trails.

What we are looking for

• 7 to 10 years of professional software engineering experience, with at least 3 years in a client-facing delivery role such as forward deployed engineering, professional services, technical consulting or an embedded engineering team at a financial institution.
• A track record of shipping systems that are running in production today. You should be able to walk us through two or three of them in detail, including what went wrong.
• Strong Python. Working proficiency in at least one of TypeScript, Java or Go. Solid SQL and comfort working with large, messy enterprise datasets.
• Hands-on experience building with large language models in production over the last two years: prompt design, structured outputs, tool calling, agent orchestration, retrieval augmented generation, and evaluation. You have opinions about what works and what does not, formed from your own deployments rather than from reading about them.
• Experience with at least one major cloud platform (AWS, Azure or GCP) including its AI services, plus the surrounding infrastructure: containers, CI/CD, secrets management, logging and observability.
• Familiarity with how regulated financial institutions govern technology: model risk management, data classification, access control, change approval and audit requirements. You do not need to have run a model validation, but you need to know why it exists and how to build something that will pass one.
• The ability to break an ambiguous business problem into a scoped, sequenced plan and to keep delivering while the requirements shift underneath you.
• Clear written and spoken communication with both engineers and senior business stakeholders. You can write the design document and also present it to a managing director in ten minutes.
• Willingness to s…