Full-Stack Engineer – AI Agent Platform (Fraud, Risk & AML)

AI in this role

langchainlanggraphbedrock

ai-agents

Shape the future of trust in the age of AI
At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place.

Why join us:

Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.
Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.
Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.

Job Description

We’re now building a new AI Agent Platform to supercharge this mission — creating intelligent, autonomous systems that proactively surface insights, act on risk events, and continuously learn from billions of signals across our data engine.

We’re looking for engineers who think fast, prototype faster, and love solving open-ended problems at the intersection of AI, full-stack development, and risk intelligence.

What You’ll Do

Design and build full-stack systems powering Oscilar’s next-gen AI agents — from backend APIs and data pipelines to fast, interactive frontends.
Implement serverless architectures using AWS Lambda and Python for high-scale, event-driven processing of risk signals and fraud patterns.
Experiment with agentic frameworks, LLM-driven automation, and reasoning systems to address fraud, risk scoring, and AML-related challenges.
Collaborate directly with founders and product leaders to shape the architecture and roadmap of our agentic platform.
Move fast — ship MVPs, test hypotheses with production data, and iterate weekly.
Apply practical AI — using GenAI, embeddings, and retrieval pipelines for data storytelling, graph reasoning, and case automation.

What You’ll Bring

4+ years of experience as a Full-Stack or Backend Engineer (TypeScript, Python, React, Node, or similar).
Proven ability to take products from zero to one in fast-moving environments.
Strong understanding of distributed systems, system design, and cloud-native architectures (AWS / Kubernetes / modern CI/CD).
Curiosity and hacker mentality — you learn new tools quickly and aren’t afraid to dive deep.
Bonus: Experience with AWS Bedrock for building and scaling generative AI applications.
Bonus: experience with LLM frameworks (LangGraph, Guardrails, LangChain, etc.) or building multi-agent or autonomous workflows.

Bonus: background in financial risk, real-time decisioning, or fraud detection systems.

Benefits

Compensation: Competitive salary and equity packages, including a 401k
Flexibility: Remote-first culture — work from anywhere
Health: 100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
Balance: Unlimited PTO policy
Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product
Culture: Family-Friendly environment; Regular team events and offsites
Development: Unparalleled learning and professional development opportunities
Impact: Making the internet safer by protecting online transactions

How we score this

Full-Stack Engineer – AI Agent Platform (Fraud, Risk & AML) at Oscilar.com scores 89 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI AgentsLangChainLangGraphBedrock

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used LangChain in your day-to-day work.
What are the limits of LangGraph that you've run into, and how did you work around them?
What's a project where you used Bedrock hands-on?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: AI Agents, LangChain, LangGraph, and Bedrock. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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