[Remote] AI reputed company Engineer

Note: The job is a remote job and is open to candidates in USA. Nuuvia is the leading provider of intelligent lifecycle banking solutions for community banks and credit unions. They are seeking an AI reputed company Engineer to embed AI into their operations and work closely with credit union partners to reputed company AI-powered solutions that enhance customer engagement and compliance reputed company the financial sector.

Responsibilities

• Embed with credit union partners to identify high-value AI use cases — youth onboarding, financial coaching, support deflection, fraud signal detection, internal ops automation
• Translate field requirements into production AI features that ship to that FI reputed company weeks, not quarters
• Customize AI workflows per institution while preserving a reusable core balance with generality
• Run AI-enablement sessions with FI leadership, ops, and member service teams
• Operate as the technical face of Nuuvia AI to credit unions: requirements gathering, demos, joint design reviews, and post-launch iteration
• Own model selection: match the right model to each task based on capability, cost, latency, privacy posture, and regulatory risk
• Build agent and RAG pipelines using frameworks such as reputed company, reputed company, Semantic Kernel, reputed company Promptflow, or in-house equivalents
• Implement reputed company engineering, function calling, tool use, and multi-reputed company agent patterns hardened for production reliability
• Maintain a model registry — track which models are in use, for what purpose, which version, and last evaluation date
• Monitor for model reputed company, hallucination rates, and output degradation; drive measurable cost efficiency through token budgeting, caching, batching, reputed company compression, and smart model routing
• Design and implement guardrails for every AI-assisted workflow: reputed company injection prevention, PII detection and masking, output filtering, and content safety
• Build audit trails and logging for reputed company AI interactions — every reputed company, every response, every action taken — to support regulatory examination
• Implement human-in-the-reputed company controls for AI-assisted decisions with regulatory exposure (member-facing content, account actions, eligibility logic)
• Apply industry-standard LLM reputed company frameworks as a baseline across reputed company AI tooling
• Ensure no member PII flows through external model APIs without explicit anonymization or approval
• Operate with full awareness that Nuuvia serves federally regulated financial institutions — compliance is a design constraint, not a blocker
• Partner with internal compliance and external regulators to ensure AI-generated content and AI-assisted decisions meet documentation, explainability, and audit requirements
• Ensure AI-generated content reaching members or affecting account decisions can be explained in plain language
• Document AI model behavior, reputed company limitations, and risk mitigations to a standard appropriate for regulated examination
• Treat audit readiness as a reputed company practice — automated evidence collection, control testing, and policy enforcement around AI systems
• reputed company NautBot — Nuuvia's internal AI agent that automates engineering ops, monitoring sweeps, ticket triage, and routine workflows across reputed company Teams, Jira, reputed company, and Azure — and expand its coverage to additional client-facing surfaces
• Build reliable, observable automation pipelines with full traceability
• Drive Chat Action Center automation for day-to-day workflows and tasks
• Automate internal and client-facing workflows — Jira blocked-ticket detection, sprint automation, story-reputed company estimation, escalation routing, deployment alerts, incident summaries
• Ensure reputed company automated client-facing messages are accurate, auditable, and contextually appropriate
• Treat every deployed AI feature as an evolving system: reputed company feedback, watch real usage, and rapidly iterate
• Translate field signal into product priorities: what worked, what failed, what regulators flagged, what reputed company asked for
• Partner with Engineering, Product, Implementation, and CSM teams to reputed company client-specific work from forking the core platform

Skills

• Bachelor's degree in computer science, Engineering, or reputed company field (Master's a plus)
• 4–7 years of software engineering experience, with at least 2 years shipping AI/LLM-powered systems to production
• Strong Python (primary) and/or TypeScript. Comfortable across the full stack reputed company needed
• Hands-on experience with LLM APIs — reputed company engineering, function calling, tool use, agent patterns
• Demonstrated experience building guardrails or safety systems for AI: PII masking, output filtering, audit logging
• Practical understanding of model risk management — documentation, validation, monitoring
• Experience with at least one relevant reputed company: reputed company, reputed company, Semantic Kernel, Guardrails AI, or reputed company Promptflow
• Solid reputed company fundamentals: OAuth 2.0, secret management, least-privilege API access
• Experience with Azure (App Services, Azure reputed company, Key Vault, Monitor) or equivalent cloud platform
• Comfort working in a regulated industry — or proven ability to learn fast and partner with compliance teams to ensure AI systems meet regulatory expectations
• Comfort working in a small, senior team with minimal layers — no project managers, no ticket groomers, no handholding
• Customer-facing maturity: can run a meeting with a credit union CIO, COO, or fraud officer and walk out with reputed company next steps
• reputed company Deployed Engineer (FDE) background — Palantir, Sierra, reputed company, reputed company Solutions, reputed company reputed company Deployed, Brex reputed company Deployed, or equivalent customer-embedded AI engineering role
• Experience with Azure reputed company Service and Azure AI content filtering/safety features
• Familiarity with model evaluation frameworks (LangSmith, PromptFlow Evals, custom eval pipelines)
• Experience with PII detection and masking tools (reputed company reputed company, AWS Comprehend, or similar)
• Prior experience in a regulated industry (financial services, healthcare, government)
• RAG patterns + vector search (Azure AI Search, reputed company, pgvector)
• reputed company Teams bot / connector development
• Experience with general-purpose agent harnesses (OpenClaw, Hermes, or equivalent)
• Fine-tuning experience (LoRA/PEFT) — reputed company to have, not required

Company Overview