Senior GenAI Backend Platform Developer

Below is a concise, ready‑to‑use snapshot of the Senior GenAI Backend Platform Developer role at FINRA. You can copy‑paste it into a notes document, a recruiter email, or a personal “job‑board” posting. I’ve also added a quick checklist of how to tailor your résumé and a few interview‑prep pointers that map directly to the most‑important requirements.

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📄 Senior GenAI Backend Platform Developer – FINRA (Regulatory Chat Assistant)

Category	Key Points
Core Mission	Build and maintain scalable, cloud‑native backend services (MCP servers, agents, tools) that enable large‑language‑model (LLM)‑driven regulatory assistance.
Primary Technical Stack	• Python (FastAPI, asyncio) • AWS – Bedrock, S3, Fargate, Lambda, Step Functions, IAM, CloudWatch • Containers – Docker (ECR/ECS/Fargate) • CI/CD – Jenkins, Git, GitHub Actions • Testing – pytest, unittest, integration test harnesses • Databases – PostgreSQL / Aurora, DynamoDB (as needed) • LLM Frameworks – LangGraph, AWS Strands, Google ADK (exposure) • Optional – C++ (preferred but not required)
Major Responsibilities	1. Design & implement MCP servers, agentic workflows, and tooling that extend LLM capabilities for regulatory use‑cases. 2. Develop cloud‑native components on AWS (Bedrock, Fargate, Lambda, Step Functions). 3. Write production‑grade code with TDD, unit & integration tests, and maintain high coverage. 4. Own CI/CD pipelines (Jenkins, Docker builds, automated deployments). 5. Collaborate in code reviews, requirement grooming, and cross‑functional design sessions. 6. Secure & compliant development – handle PII, follow FINRA security standards, participate in threat modeling. 7. Stay current on LLM advances, optimization techniques, and emerging AI frameworks.
Quality & Testing	• Test‑driven development (pytest, coverage ≥ 80%). • Automated integration tests for end‑to‑end LLM pipelines. • Continuous monitoring of performance & security metrics.
DevOps / Infra	• Build/maintain Jenkins pipelines (build → test → container → deploy). • Dockerize services; understand ECS/Fargate orchestration. • Use IaC (CloudFormation / CDK) for repeatable AWS deployments.
Collaboration	• Peer reviews of specs & code. • Clear documentation (README, API spec, design docs). • Communicate technical concepts to both engineers and non‑technical stakeholders.
Security & Compliance	• Secure coding (OWASP, least‑privilege IAM). • Data‑privacy handling for regulatory data (PII, FINRA‑specific). • Participate in FINRA‑mandated threat‑modeling sessions.
Learning & Growth	• Rapidly acquire new skills (e.g., LangGraph, AWS Strands). • Seek mentorship; give constructive feedback.
Education / Experience	• BS in CS/Info‑Systems or equivalent experience. • 5+ years of backend/enterprise software development. • Strong OOP, DB design, Agile delivery. • Preferred: C++ exposure, prior work with LLM‑centric products.
Location / Salary	• Hybrid (office days defined by team). • Salary ranges (2026):  - San Francisco: $144.6k – $211.4k  - CO/FL/TX: $97.7k – $176.1k  - IL/PA: $107.5k – $194.1k  - MA/MD/VA/DC: $112.3k – $202.5k  - NY/NJ: $112.3k – $211.4k
Benefits	• Discretionary bonus, overtime (non‑exempt). • Health/Dental/Vision, life & AD&D, 401(k) match, tuition reimbursement, commuter benefits, wellness programs, generous PTO (15 days + 5 personal + 9 sick). • Volunteer days, parental leave, military/jury/bereavement leave, etc.
Compliance Notes	• Must sign FINRA Confidentiality & Invention Assignment Agreement. • Must disclose all brokerage accounts & adhere to FINRA investment restrictions. • No unsolicited search‑firm resumes accepted.

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🛠️ How to Tailor Your Résumé (quick checklist)

FINRA Requirement	Resume Action
Python + FastAPI + AWS	Highlight any production services built with FastAPI, Lambda, Fargate, or Bedrock. Include metrics (e.g., “Reduced API latency 30 % via async FastAPI + Lambda”).
Test‑Driven Development	List “TDD (pytest, 85 % coverage) on X micro‑services” and any CI test‑pipeline contributions.
CI/CD (Jenkins, Docker)	Show “Designed Jenkins pipeline for automated Docker builds & Canary deployments to ECS”.
LLM Integration	Mention projects that used LangChain, LangGraph, or custom LLM wrappers; note any work with regulatory or compliance data.
Security/Compliance	Cite “Implemented IAM least‑privilege policies, encrypted S3 buckets, and performed threat‑modeling for PII‑handling APIs”.
Collaboration & Agile	Include “Scrum team member, participated in sprint planning, code reviews, and cross‑functional design workshops”.
C++ (preferred)	If you have any C++ experience (even a side‑project), list it under “Additional Languages”.
Regulatory/Financial Domain	If you’ve worked in fintech, banking, or any regulated environment, make that explicit.
Education	BS in CS (or equivalent) – list graduation year, GPA if strong, relevant coursework (Distributed Systems, Security).
Location	Add “Open to hybrid work in [city/state]” and ensure your address aligns with the salary band you’re targeting.

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🎤 Interview‑Prep Focus Areas

Topic	Suggested Talking Points
LLM‑centric backend design	Explain how you’d architect a “Regulatory‑Chat” service: FastAPI gateway → Lambda orchestrator → Bedrock LLM → Step Functions for multi‑turn workflow. Emphasize latency, cost‑control, and audit logging.
TDD & Quality	Walk through a recent feature you built using TDD: write failing test → minimal code → refactor → achieve coverage. Mention tools (pytest‑cov, mock, moto for AWS).
CI/CD pipeline	Detail a Jenkins pipeline you built: stages (checkout → lint → unit test → Docker build → security scan → deploy to dev). Highlight any “blue‑green” or “canary” strategies you used.
Security & FINRA compliance	Discuss handling of PII: encryption at rest/in‑transit, IAM policies, data‑masking, audit logs, and how you’d integrate with FINRA’s threat‑modeling process.
Scalable AWS architecture	Talk about using Fargate for containerized services, Step Functions for orchestrating multi‑step LLM workflows, and S3 for model artefacts. Show cost‑optimization (e.g., using Spot for batch jobs).
Collaboration	Provide an example of a cross‑functional design review where you helped translate regulatory requirements into technical specs.
Learning agility	Mention a recent technology you self‑studied (e.g., LangGraph) and built a PoC within a week. Show your “rapid‑skill‑acquisition” mindset.
C++ (if applicable)	Even a modest exposure is fine – describe a C++ module you maintained or a performance‑critical component you optimized.
Regulatory domain knowledge	If you have any exposure to FINRA rules, SEC filings, or compliance workflows, weave that into your answers.

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📌 Quick “Elevator Pitch” (30 seconds)

“I’m a senior backend engineer with 6 years of experience building cloud‑native, Python‑centric services on AWS. I’ve led the design of FastAPI‑driven micro‑services that integrate LLMs via Bedrock, using Step Functions for multi‑turn workflows, and I practice test‑driven development with > 80 % coverage. I’m comfortable automating the full CI/CD lifecycle in Jenkins/Docker, and I’ve implemented secure, compliant data pipelines that meet strict financial‑industry standards. I’m excited to bring my expertise in scalable AI‑backends and my passion for regulatory technology to FINRA’s GenAI platform.”

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Next Steps

1. Update your résumé using the checklist above.
2. Draft a cover letter that mirrors the “Elevator Pitch” and ties your experience to FINRA’s mission (regulatory chat assistant).
3. Apply via the FINRA Careers portal (or the direct link you already have).
4. Prepare the interview talking points and a few concrete code‑samples or GitHub repos you can discuss (preferably with AWS/LLM components).

Good luck! 🎉 If you’d like a deeper dive into any of the technical topics (e.g., a sample FastAPI + Bedrock integration) or need help polishing your résumé, just let me know.