AI Workflow Engineer

Job Description

Job Description

Accertify enables commerce by doing one thing extraordinarily well: pinpointing fraud. The company's Predictive Yes Platform helps businesses say yes to more - more good customers, more revenue, and more growth - without getting burned. It's a precise, confident, data-backed yes, made possible by joining signals across the entire customer lifecycle through unmatched data volume, layered AI-powered models, and a consortium approach that protects clients from bad actors spotted anywhere in the network while unlocking business with good actors verified anywhere in the network. With more than 10 billion transactions and over $1 trillion in commerce processed in 2025 alone, Accertify delivers the intelligence and precision that fraud and payments teams need to say yes confidently and enable growth. That's the More Yes difference.

We're looking for a Workflow Engineer who turns AI capabilities into production-grade agent workflows that automate real business processes. You'll design and ship LLM-powered flows, from RAG pipelines and MCP tools to multi-step agentic automations, and integrate them safely with our apps, data, and APIs. You'll work closely with product, platform, and security to deliver fast, reliable, and cost-efficient AI outcomes.

Essential Duties & Responsibilities:

Build agentic systems

• Design and implement agent workflows using tools like LangGraph, CrewAI, n8n (or similar)
• Create task decomposition, tool-use policies, guardrails, and evaluation loops

Implement Retrieval-Augmented Generation (RAG)

• Stand up vector search and retrieval pipelines; select embedding strategies
• Optimize context packing, grounding quality, and hallucination mitigation

Develop MCP tools & integrations

• Build Model Context Protocol (MCP) servers and custom tools to safely connect to APIs, databases, and internal systems
• Establish capabilities, permissions, and auditing for tool use

Ship production-ready AI services

• Build FastAPI/Node services that expose AI workflows behind secure APIs
• Own CI/CD for workflow services; write tests, contract checks, and evals.

Measure and improve

• Instrument workflows with latency, cost, accuracy, and safety metrics
• Run prompt/eval experiments; iterate on prompts, memory, and grounding

Partner across teams

• Work with product & ops to prioritize use cases
• Collaborate with Platform/DevOps to deploy and scale reliably in Kubernetes

Skills & Qualifications:

• Strong coding in Python and/or Node; clean API design
• Hands-on with LLM integration (prompting, tool use, function calling)
• Experience building RAG systems and working with vector databases.
• Practical familiarity with LangGraph/CrewAI/n8n or similar orchestration.
• Experience building MCP tools/servers or equivalent agent-tool frameworks
• Solid understanding of REST/GraphQL, auth (OAuth/OIDC), and secure integration.
• Containers, Git, CI/CD basics; comfort shipping production services.

Preferred Qualifications:

• Evals & guardrails (e.g., structured output, JSON schemas, toxicity/PII checks)
• Knowledge graphs / event-driven architectures/workflow engines
• Model selection & optimization; prompt caching; cost/perf tuning
• Exposure to LLM safety, privacy, governance, and enterprise compliance

Additional Details:

• Potential Salary Range: $115,000 to $120,000. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations.
• This role is eligible for remote US-based (work-from-home) locations. Chicago-based candidates would work in a hybrid capacity from Accertify's HQ in Itasca, IL.
• Visa Sponsorship: Employment eligibility to work for Accertify in the U.S. is required, as Accertify will not pursue Visa sponsorship for this position.

Why Join Accertify?

Employees are eligible for Accertify’s comprehensive benefits package, including medical, dental, and vision coverage; paid time off; and wellness programs. Employees may also participate in retirement programs, including a 401(k) plan with company matching contributions, subject to plan terms and eligibility requirements.