Staff Engineer, AI & Agentic Development

See Job posting on www.DKKDstaffing.com for full job description

CITIZENSHIP: Must be US Citizen or Legal/Permanent Resident Green Card (no C2C)

TITLE: Staff Engineer, AI & Agentic Development

LOCATION(S): #1 Dallas, # 2 NYC and then last resort remote/hybrid from near Dallas.

IN OFFICE POLICY IF LOCAL TO NY or TX location: If local, 4 days a week onsite. If not local, arrangements for 2-3 days a week in office, or possibly remote for a perfect candidate

SALARY RANGES: $200 – $225K

HIERARCHY/REPORT TO: Director of Engineering and Partner

SIZES OF STAFF TO MANAGE: none at first, but proven experience mentoring and building a development team

EDUCATION/ DEGREES/ CERTIFICATIONS REQUIRED: Bachelors

INDUSTRY: Fintech, Banking, Financial Services Platforms, Start-ups

PRIVATE COMPANY

# of EMPLOYEES: <200 and growing

CITIZENSHIP: Must be US Citizen or Legal/Permanent Resident Green Card (no C2C)

REQUIREMENTS:

• This is not an ML research role—it is a product engineering role for someone who can take large language models, tool-use patterns, and agentic frameworks and ship them as reliable, production-grade features that financial operations teams depend on daily.
• You will work across the below following stack. Deep expertise in every layer is not required—but you should be comfortable navigating a polyglot codebase and making architectural decisions that span these technologies.
• 8 years of professional software engineering experience, with significant time spent building production systems at scale.
• 3 years of hands-on experience building AI/ML-powered product features—not research prototypes, but shipped, production software that real users depend on.
• Deep experience with LLM integration: prompt engineering, function/tool calling, RAG architectures, agent orchestration, and evaluation frameworks.
• Strong software engineering fundamentals: system design, API design, data modeling, distributed systems, and production operations.
• Experience with at least one modern AI/agent framework (LangChain, LlamaIndex, Anthropic tool use, OpenAI Assistants, CrewAI, or similar) and a clear-eyed view of their trade-offs.
• Proficiency in Python and/or TypeScript. Familiarity with SQL and relational databases.
• Track record of leading technical initiatives that span multiple teams or systems, with strong written communication (RFCs, design docs, ADRs).
• Demonstrated ability to work with ambiguity—translating broad product goals into concrete technical plans and shipping iteratively.

PREFERRED QUALIFICATIONS

• Experience building MCP servers or integrations, or deep familiarity with the Model Context Protocol ecosystem.
• Domain experience in FinTech, payments, accounting automation, fund administration, or financial operations.
• Experience with AI-assisted development tools (Claude Code, Cursor, Copilot) and a philosophy for how they change engineering workflows.
• Background in building trust and safety systems for AI: content filtering, output validation, human-in-the-loop patterns, and audit logging for autonomous actions.
• Experience with Azure cloud services, SQL Server, or Azure DevOps.
• Familiarity with financial data formats and integrations: NACHA, ISO 20022, SWIFT, or accounting system APIs (QuickBooks, NetSuite, Sage).
• Prior experience at a Staff/Principal level or as a founding/early engineer at a startup where you shaped technical direction.

JOB SCREENING QUESTIONS – Part 2

Please answer next to each question and send to Di@DKKDstaffing.com

• How many years of experience and how recent is your experience in a SaaS financial environment:
• How many years of experience and how recent is your experience in a Product Engineering role taking large language models, tool-use patterns, and agentic frameworks and ship them as reliable, production-grade features that financial operations teams depend on daily:
• How many years of professional software engineering experience, with significant time spent building production systems at scale, and most recent year:
• How many years of hands-on experience building AI/ML-powered product features—not research prototypes, but shipped, production software that real users depend on, and most recent year:
• How many years of deep experience do you have with LLM integration: prompt engineering, function/tool calling, RAG architectures, agent orchestration, and evaluation frameworks, and most recent year:
• How many years of experience do you have with software engineering fundamentals: system design, API design, data modeling, distributed systems, and production operations, and most recent year:
• How many years of experience do you have with at least one modern AI/agent framework (LangChain, LlamaIndex, Anthropic tool use, OpenAI Assistants, CrewAI, or similar) and a clear-eyed view of their trade-offs, and most recent year:
• How many years of experience do you have with Python and/or TypeScript. Familiarity with SQL and relational databases, and most recent year:
• How many years of experience do you have leading technical initiatives that span multiple teams or systems, with strong written communication (RFCs, design docs, ADRs) , and most recent year:
• How many years of experience do you have with Demonstrated ability to work with ambiguity—translating broad product goals into concrete technical plans and shipping iteratively, and most recent year:
• How many years of experience do you have building MCP servers or integrations, or deep familiarity with the Model Context Protocol ecosystem, and most recent year:
• How many years of experience do you have with Domain experience in FinTech, payments, accounting automation, fund administration, or financial operations, and most recent year:
• How many years of experience do you have with AI-assisted development tools (Claude Code, Cursor, Copilot) and a philosophy for how they change engineering workflows, and most recent year:
• How many years of experience do you have with building trust and safety systems for AI: content filtering, output validation, human-in-the-loop patterns, and audit logging for autonomous actions
• How many years of experience do you have with Azure cloud services, SQL Server, or Azure DevOps, and most recent year:
• How many years of experience do you have with financial data formats and integrations: NACHA, ISO 20022, SWIFT, or accounting system APIs (QuickBooks, NetSuite, Sage), and most recent year:
• How many years of experience do you have at a Staff/Principal level or as a founding/early engineer at a startup where you shaped technical direction, and most recent year:

OVERVIEW

Our client has a SaaS platform that automates accounts-payable workflows, payment processing, and financial operations for hedge funds, private equity firms, fund administrators and family offices. The platform handles invoice capture, approval routing, vendor management, multi-entity accounting, and payment execution.

They are entering a new phase of product development: embedding AI and agentic capabilities directly into their platform to transform how financial operations teams work. This is the most important technical initiative for our client, and this role will lead it.

About the Role

We are hiring a Staff Engineer to own the architecture, design, and delivery of AI-powered and agentic features. This is not an ML research role—it is a product engineering role for someone who can take large language models, tool-use patterns, and agentic frameworks and ship them as reliable, production-grade features that financial operations teams depend on daily.

You will define how AI is integrated into the SaaS platform: which workflows become agentic, how models interact with our domain data, how we build trust and safety into autonomous financial operations, and how we evolve the platform architecture to support these capabilities at scale.

This is a high-autonomy, high-impact role. You will work across the full stack—from prompt engineering and model orchestration to API design, data pipelines, and frontend integration—and collaborate closely with product, design, and domain experts to ship features that meaningfully change how our clients operate.

Key Responsibilities

Agentic Architecture & System Design

AI Feature Development

Technical Leadership

Cross-Functional Collaboration