Interested in this AI Agent Developer role at FINRA?
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About This Role
Working independently, the Lead Engineer owns development of software products and works on improving the overall quality of the product throughout the software development life cycle and mentors other Software Engineers. Reports directly to a Director or Senior Director.Overview:
- Architects and builds the infrastructure and tooling that powers AI agent development across the Software Development Lifecycle (SDLC).
- Develops production\-grade agentic systems, orchestration frameworks, and observability solutions that enable teams to build, deploy, and monitor reliable AI agents at scale.
- Plays a key role in defining and implementing the next generation of SDLC through AI\-first innovation and comprehensive instrumentation.
What We're Looking For:
- You demonstrate sharp product sense for high\-impact automation opportunities, technical taste in implementation decisions, and the ability to clearly articulate trade\-offs. You know when to apply AI agent solutions versus simpler approaches and can explain the "why" behind architectural choices.
- You excel at 0\-to\-1 (and 1\-to\-100\) product development, comfortable operating in ambiguous environments where requirements emerge through experimentation and iteration rather than upfront specification.
Key Responsibilities:
AI Agent Development \& Automation
- Develop production\-grade AI agents that eliminate manual handoffs across the SDLC
- Create custom integrations and CLI tools that give agents deep understanding of internal systems and codebases
- Design comprehensive testing strategies to ensure agent reliability and output quality
- Implement "Golden Path" scaffolding that embeds organizational standards into new projects
- Build AI solutions that improve codebase navigation, documentation, and developer workflows
- Identify workflow bottlenecks and deliver measurable impact through intelligent automation
- Shape SDLC evolution by identifying AI\-first opportunities and proving outcomes through experimentation
Agent Infrastructure \& Platform:
- Architect and maintain production infrastructure supporting agent deployment, lifecycle management, and scaling
- Develop agent frameworks, templates, and SDKs that accelerate agent development
- Create governed Model Context Protocol (MCP) catalog enabling compliant agent\-to\-agent and agent\-to\-MCP communication
- Implement governance controls for agent behavior, permissions, and system access
Observability \& Performance Analytics:
- Design and implement metrics, monitoring, and logging infrastructure for AI agents and development workflows
- Build dashboards that provide actionable insights into developer productivity, tool adoption, and agent performance
- Establish KPIs and measurement frameworks to quantify the impact of AI\-powered automation
- Create alerting and anomaly detection systems to ensure reliability of agents and tooling
- Analyze telemetry data to identify optimization opportunities and guide strategic investment decisions
Collaboration \& Impact:
- Partner across teams to drive adoption of AI\-powered tooling and process transformation
- Stay current with LLM technologies and coach colleagues on AI\-assisted development and automation best practices
- Rapidly prototype solutions to validate use cases and prove value quickly
- Communicate data\-driven insights to stakeholders through clear visualizations and reports
Full\-stack technical proficiency:
- Languages: Java, Python, JavaScript/TypeScript
- Frameworks: Angular, Spring Boot
- CI/CD platforms and cloud infrastructure (AWS)
- Monitoring/observability tools (e.g., Prometheus, Grafana, CloudWatch)
Education/Experience Requirements:
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- Bachelor’s degree in Computer Science, Information Systems or related discipline with at least 7 years of related experience, or equivalent training and/or work experience.
- Strong system design experience
- Strong experience in object\-oriented development
- Strong experience with cloud technologies
- Strong experience in data storage technologies
- Strong experience in performance tuning and optimization
- Strong experience in DevOps and CI\\CD technologies
- Strong experience test automation and unit testing
- Strong experience software security
Working Conditions:
- Hybrid work environment, with defined in\-person presence requirements.
- Occasional travel and extended hours may be required.
For work that is performed in CO, FL, TX, IL, PA, MA, MD, VA, Washington, DC, NY and NJ, please refer to the chart below for the salary range for the corresponding location. FINRA complies with all state and local pay transparency laws and regulations requiring the disclosure of salary ranges for the position. In addition to location, actual compensation is based on various factors, including but not limited to, the candidate’s skill set, level of experience, education, and market considerations.
CO/FL/TX: Minimum Salary $114,200, Maximum Salary $207,200
IL/PA: Minimum Salary $125,900, Maximum Salary $228,000
MA/MD/VA/Washington, DC: Minimum Salary $131,200, Maximum Salary $238,300
NY/NJ: Minimum Salary $131,200, Maximum Salary $248,700
\#LI\-Hybrid
To be considered for this position, please submit an application. Applications are accepted on an ongoing basis.
*The information provided above has been designed to indicate the general nature and level of work of the position. It is not a comprehensive inventory of all duties, responsibilities and qualifications required.*
*Please note: If the “Apply Now” button on a job board posting does not take you directly to the FINRA Careers site, enter www.finra.org/careers into your browser to reach our site directly.*
Employees may be eligible for a discretionary bonus in addition to base pay. Non\-exempt employees are also eligible for overtime pay in accordance with federal, state, or local law. As part of its dedication to employee wellness, FINRA provides comprehensive health, dental and vision insurance. Additional insurance includes basic life, accidental death and dismemberment, supplemental life, spouse/domestic partner and dependent life, and spouse/domestic partner and dependent accidental death and dismemberment, short\- and long\-term disability, long\-term care, business travel accident, disability and legal. FINRA offers immediate participation and vesting in a 401(k) plan with company match and eligibility for participation in an additional FINRA\-funded retirement contribution, tuition reimbursement, commuter benefits, and other benefits that support employee wellness, such as adoption assistance, backup family care, surrogacy benefits, employee assistance, and wellness programs.
Time Off and Paid Leave\*
FINRA encourages its employees to focus on their health and wellness in many ways, including through a generous time\-off program of 15 days of paid time off, 5 personal days and 9 sick days, unless otherwise required by law (all pro\-rated in the first year). Additionally, we are proud to support our communities by providing two volunteer service days (based on full\-time schedule). Other paid leave includes military leave, jury duty leave, bereavement leave, voting and election official leave for federal, state or local primary and general elections, care of a family member leave (available after 90 days of employment); and childbirth and parental leave (available after 90 days of employment). Full\-time employees receive nine paid holidays.
- Based on full\-time schedule
Important Information
FINRA’s Code of Conduct imposes restrictions on employees’ investments and requires financial disclosures that are uniquely related to our role as a securities regulator. FINRA employees are required to disclose to FINRA all brokerage accounts that they maintain, and those in which they control trading or have a financial interest (including any trust account of which they are a trustee or beneficiary and all accounts of a spouse, domestic partner or minor child who lives with the employee) and to authorize their broker\-dealers to provide FINRA with duplicate statements for all of those accounts. All of those accounts are subject to the Code’s investment and securities account restrictions, and new employees must comply with those investment restrictions—including disposing of any security issued by a company on FINRA’s Prohibited Company List or obtaining a written waiver from their Executive Vice President—by the date they begin employment with FINRA. Employees may only maintain securities accounts that must be disclosed to FINRA at one or more securities firms that provide an electronic feed (e\-feed) of data to FINRA, and must move securities accounts from other securities firms to a firm that provides an e\-feed within three months of beginning employment.
You can read more about these restrictions here.
As standard practice, employees must also execute FINRA’s Employee Confidentiality and Invention Assignment Agreement without qualification or modification and comply with the company’s policy on nepotism.
Search Firm Representatives
Please be advised that FINRA is not seeking assistance or accepting unsolicited resumes from search firms for this employment opportunity. Regardless of past practice, a valid written agreement and task order must be in place before any resumes are submitted to FINRA. All resumes submitted by search firms to any employee at FINRA without a valid written agreement and task order in place will be deemed the sole property of FINRA and no fee will be paid in the event that person is hired by FINRA.
FINRA is an Equal Opportunity Employer
All qualified applicants receive consideration for employment without regard to any legally protected category, including race, color, age, national origin, ethnicity, religion, disability, genetic information, military or veteran status, sex, or any other status or classification protected by state or local law.
FINRA strives to make our career site accessible to all users. If you need a disability\-related accommodation for completing the application process, please contact FINRA’s Employee Relations team at 240\-386\-4865 or by email at [email protected]. Please note that this process is exclusively for inquiries regarding accommodations in the application process.
FINRA abides by the requirements of 41 CFR 60\-741\.5(a). This regulation prohibits discrimination against qualified individuals on the basis of disability and requires affirmative action by covered prime contractors and subcontractors to employ and advance in employment qualified individuals with disabilities.
FINRA abides by the requirements of 41 CFR 60\-300\.5(a). This regulation prohibits discrimination against qualified protected veterans and requires affirmative action by covered prime contractors and subcontractors to employ and advance in employment qualified protected veterans.
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Salary Context
This $114K-$248K range is below the median for AI Agent Developer roles in our dataset (median: $212K across 45 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 3,824 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At FINRA, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $252,000 based on 90 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($181K) sits 28% below the category median. Disclosed range: $114K to $248K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
FINRA AI Hiring
FINRA has 2 open AI roles right now. They're hiring across AI Agent Developer, AI/ML Engineer. Positions span McLean, VA, US, Rockville, MD, US. Compensation range: $248K - $248K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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