Senior AI Full-Stack Engineer

Broadview Federal Credit Union•Albany, NY

7d•$115,000 - $150,000

About The Position

Broadview is establishing its first dedicated AI function. This role is for someone who can transform AI capabilities into practical products for users, focusing on production applications rather than just pilots or proofs of concept. The goal is to ship secure applications to employees and members quickly. The position offers the opportunity to build the first AI applications within the company, working on a small, senior, high-autonomy team alongside the VP of Artificial Intelligence and an AI Automation & Solutions Architect. There is no existing AI codebase to maintain or backlog to inherit.

Requirements

Bachelor's degree in Computer Science, Information Systems/Technology, Data Science, Math, Electrical Engineering, or Machine Learning (Artificial Intelligence).
7+ years building and shipping production software.
At least 2 years building AI or LLM-based applications that real users depend on.
Genuine full-stack depth: modern TypeScript/React or equivalent on the front end, Python or TypeScript services on the back end, relational and vector data stores, and cloud deployment experience owned in production.
Hands-on fluency with LLM application patterns: prompt design, structured output, tool use and function calling, retrieval and reranking, agentic orchestration, context management, and cost and latency optimization.
Demonstrated LLM evaluation experience: experience building test sets, measuring output quality, and catching regressions before users do.
Working knowledge of AI-specific security: prompt injection, data exfiltration, data and model poisoning, model access control, and secrets management.
Product instinct: Ability to understand user workflows and design adoptable AI solutions to improve their work and member experience.

Nice To Haves

Experience delivering in a regulated environment (e.g., financial services, healthcare, insurance, government).
Working knowledge of model risk management, third-party risk review, and audit or examination cycles.
Integration experience with core banking, loan origination, or payments platforms.
Professional familiarity with enterprise iPaaS (Workato, MuleSoft, Boomi), Anthropic, and AWS Bedrock.
Fine-tuning, distillation, or self-hosted small-model deployment experience.
Contributions to open-source AI tooling, or public technical writing on LLM application engineering.

Responsibilities

Full-vertical delivery: Build and ship secure production AI applications end to end, including assessing data access, model orchestration, API layer, and user interfaces.
Design and implement agentic workflows: Create multi-step, tool-using systems that retrieve, reason, act, and hand off to humans when appropriate, determining when deterministic workflows are more suitable than probabilistic ones.
Build RAG pipelines: Develop retrieval-augmented generation pipelines across various internal knowledge sources like policy manuals, procedures, product documentation, and lending guidelines, ensuring measurable retrieval quality.
Evaluation before launch: Collaborate with QA teams to rigorously test all systems against regulatory, policy, and other frameworks before promotion, ensuring every AI feature includes a test set, scoring method, and regression suite.
Secure systems integration: Connect securely through documented APIs and the company's iPaaS layer.
Implement guardrails: Prioritize AI-specific security measures including prompt injection defense, PII handling, model drift and poisoning detection, output validation, human-in-the-loop checkpoints, and comprehensive audit logging.
Determine production readiness: Use judgment to decide which agentic tools and applications are ready for production hardening and which should be discarded or revisited later.
Establish engineering standards: Define and implement code review, testing, deployment pipelines, documentation, and secure development practices suitable for a federally regulated financial institution.