Description

Job Summary
The Senior Full Stack AI Engineer will design, build, and scale enterprise AI capabilities supporting portfolio management and investment research workflows. This position will serve as a hands-on technical leader, developing secure, governed, reusable agentic solutions and helping mature a shared enterprise AI platform.

Must Have Technical/Functional Skills

8+ years of experience in software engineering, automation, or platform engineering.

Hands-on experience implementing large language model-based or agentic AI solutions in enterprise environments.

Experience with Anthropic Cloud Code and advanced Claude services, including interpreter-style workflows.

Strong understanding of agent architectures, tool orchestration, and secure AI platform design.

Proficiency in Python and modern cloud-native development patterns.

Experience working with portfolio management, investment research, or quantitative analytics workflows.

Experience building AI platforms or shared AI services in financial services or regulated environments.

Experience integrating AI solutions with enterprise data platforms and analytics stacks.

Familiarity with Responsible AI frameworks, model governance, auditability, and security requirements.

Experience with tool calling, retrieval-augmented generation, structured data semantics, reusable prompts, and reusable skills.

Roles & Responsibilities

Design and build AI capabilities, agents, and reusable skills using approved platform frameworks, reference architectures, and governance controls.

Develop agentic workflows and multi-agent orchestration patterns.

Contribute to agent runtime integration, memory patterns, observability, versioning, and gated deployment models.

Establish implementation patterns for Anthropic Cloud Code, prompts, tools, reusable skills, agent safety, and policy enforcement.

Build advanced capabilities using Claude Interpreter and higher-order reasoning services.

Enable secure data exploration, analysis, multistep reasoning, and tool invocation within defined agent boundaries.

Partner with portfolio managers, research analysts, and quantitative teams to identify and implement high-value AI use cases.

Develop solutions for research summarization, scenario analysis, factor and exposure analysis, and structured and unstructured data interpretation.

Convert exploratory research solutions into repeatable, production-ready enterprise capabilities.

Integrate AI automation with CI/CD pipelines, software development lifecycle tooling, cloud platforms, and enterprise data systems.

Establish reusable AI components, frameworks, guardrails, reference architectures, and implementation patterns.

Ensure AI capabilities comply with security, auditability, cost attribution, and Responsible AI standards.

Create reference implementations, documentation, and enablement materials that support platform adoption.

Provide architectural guidance to reduce platform fragmentation and unauthorized AI implementations.

Define and track measurable improvements in productivity, quality, decision velocity, analytical depth, developer experience, and risk reduction.

Support executive visibility into AI-driven outcomes and platform maturity

Key Skills

Education

Any Graduate