Ai Engineer (Generative Ai)

About MNEE AppMNEE App is a financial technology company building simpler, faster ways for people and businesses to move and use money in the digital economy.
Our vision is to make digital finance more accessible by bringing everyday financial tools and digital assets together. MNEE App combines a checking account, debit card, and crypto in one place, giving customers a simpler way to manage their money.
We’re also building the infrastructure to make stablecoins practical for everyday commerce. Through MNEE Pay, merchants can accept stablecoin payments through their existing checkout and POS environments, with lower transaction costs, fast settlement, global reach, and no chargebacks.
We’re building at the intersection of fintech, digital assets, payments, and emerging technology, and we’re growing a global team of people who want to help shape what comes next.
We are seeking an AI Engineer with exposure to advanced analytics to join our growing generative-AI program and help expand it across the company!
About the RoleYou will build and operate LLM-powered agents and generative-AI applications, taking agentic use cases from ideation to deployment, and support the business with advanced analytics. A generative-AI advocacy mindset is welcomed.
You will be part of the Reporting and Analytics team, reporting to the Manager, Reporting & Analytics. You will work closely with teams across the company to identify high-value use cases and bring AI solutions into their daily operations.
This role is remote with a preference for applicants based in Canada and in the Eastern Time Zone (ET).
Key Responsibilities
Take agentic use cases from ideation to deployment: scope with stakeholders, prototype, evaluate, and ship to production.
Engineer the full agent stack on managed platforms such as Amazon Bedrock: prompt design, tool / function calling, retrieval-augmented generation (RAG), conversation memory and context management, and multi-agent orchestration.
Integrate AI agents into business workflows and enterprise systems — REST APIs, SQL data warehouses, messaging platforms, and third-party tools.
Build evaluation and guardrails for LLM applications: automated regression testing, output quality benchmarks, and human-in-the-loop controls.
Work with emerging agent interoperability standards — Model Context Protocol (MCP), agent-to-agent (A2A) communication, and shared agent memory.
Deliver advanced analytics — deep-dive analyses, SQL data products, and reporting that answer high-value business questions.
Stay current with the generative-AI landscape and evaluate new models, frameworks, and techniques.
Support AI adoption across teams through demos, documentation, and enablement.
How We Get Things Done – Our ICONIC ValuesOur ICONIC values shape how every RockWallet team member works. We look for a Project Manager who brings them to life every day:
Integrity
– Does the right thing, even when it’s inconvenient;
raises risks and concerns early rather than working around them, and treats customer trust and data security as non-negotiable.
Collaborative
– Works across boundaries and avoids silos;
shares information proactively, seeks input from relevant stakeholders, and prioritizes organization outcomes over individual or team wins.
Ownership
– Takes responsibility for outcomes, not just tasks;
follows through on commitments, closes loops, and thinks end-to-end about impact on customers, teams, and the business.
Nimble
– Adapts quickly while staying disciplined;
responds effectively tochange, balances speed with sound judgment and compliance, and avoids over-engineering when simpler solutions will work.
Innovative
– Continuously improves how we work and what we deliver;
challenges outdated processes and uses data, experimentation, and new tools—including AI—to drive practical improvement.
Customer
– Puts the customer at the center of decisions;
designs solutions that reduce friction and balances business goals with customer trust and experience.
Candidate Profile & Qualifications:
3 to 5+ years of experience in software engineering, machine learning engineering, or applied AI.
Strong Python and SQL skills, with the habits of a production engineer: version control, code review, testing.
Hands‑on experience shipping LLM applications: prompt engineering, function calling, RAG, and agent frameworks (e.G., LangChain, LangGraph, CrewAI, or cloud-native agent SDKs).
Experience building and running services on a major cloud (AWS preferred: Lambda, ECS, DynamoDB, S3, IAM).
Familiarity with LLM evaluation and observability — measuring quality, reliability, latency, and cost of AI systems.
Comfortable with modern engineering workflows: Git-based code review, automated testing, and CI/CD pipelines.
Awareness of security, privacy, and governance considerations when deploying AI on sensitive data.
Excellent analytical, communication, and problem‑solving skills.
Degree in Computer Science, Engineering, Data Science, or a related quantitative field.
Must be flexible and able to work in a fast‑paced, dynamic environment and adapt to changing priorities.
Nice to Have
Experience in fintech, payments, or other regulated industries.
Exposure to Model Context Protocol (MCP), Amazon Bedrock, or agent-to-agent orchestration.
Background in data science or classical machine learning (anomaly detection, forecasting, segmentation).
Experience building internal tools or integrating platforms such as Slack, CRMs, or ticketing systems.
Work from home
Diverse and dynamic work environment
Work-life balance and support for career development
We thank all interested applicants;
however, only those under consideration will be contacted.
MNEE App is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and
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