Senior GenAI Full-Stack Engineer

Description

Our client is seeking an AI Automation Engineer – SDLC & GenAI Platforms to support the continued expansion of its GenAI capabilities across Investment Technology. The written JD focuses on building and scaling AI-driven automation across the software delivery lifecycle, including requirements, design, development, testing, deployment, and auditability. The role also emphasizes Anthropic-based capabilities, agentic workflows, enterprise GenAI platforms, governance, and measurable business outcomes.

In practice, this is a full-stack AWS engineering role with a GenAI/LLM overlay. The ideal candidate is a hands-on engineer who can build cloud-native applications, integrate LLMs and agentic workflows, and work directly with investment professionals to deliver business-facing technology solutions.

The team is already operating in a mature GenAI environment, with production agents and workflows in place. This person will help build additional GenAI-enabled use cases across investment research, portfolio management, risk, SMA, onboarding, and related front-office investment workflows.

This is not a pure AI strategy, data science, MLOps, or prompt engineering role. Our client needs builders — engineers who can code, communicate, and deliver production-ready applications in a fast-moving, business-facing environment.

Key Responsibilities:

Full-Stack Application Development:

• Build and enhance cloud-native applications supporting the investment technology organization.

• Develop backend services, APIs, user interfaces, workflow tools, dashboards, and integrations using technologies such as Java, Python, React, Angular, and AWS.

• Own application functionality from business problem through design, development, testing, deployment, and support.

• Apply CI/CD, automated testing, and Test-Driven Development practices to deliver reliable production software.

GenAI / LLM Engineering:

• Design and build GenAI-enabled applications and workflows using LLMs, AI agents, RAG, prompt engineering, and model orchestration.

• Integrate AI capabilities into existing enterprise applications, SDLC tooling, CI/CD pipelines, cloud platforms, and business workflows.

• Work with AWS-based AI capabilities, including AWS Bedrock, and support model integration across multiple LLM providers.

• Leverage Anthropic / Claude capabilities where applicable, including prompt engineering standards, agent-based orchestration patterns, and secure model invocation.

Investment Technology Partnership:

• Partner directly with portfolio managers, research analysts, and investment professionals to understand business needs and build practical technology solutions.

• Translate ambiguous investment workflows into working software without relying on a traditional BA/QA-heavy handoff model.

• Support use cases across investment research, portfolio management, risk, SMA, client/sponsor onboarding, portfolio rebalancing, and investment oversight.

• Help improve the business’s ability to make investment decisions, expand research coverage, and generate measurable value.

Platform, Governance & Measurement:

• Build within a secure, governed, and auditable enterprise AI environment.

• Contribute to reusable architecture patterns, implementation standards, guardrails, and developer enablement.

• Help measure productivity, quality, cycle-time, developer experience, risk reduction, and business impact from GenAI-enabled solutions.

Skills:

LLM, GenAI, Java, Aws, python, AWS Bedrock, LLM observability, wealth management

Top Skills Details:

LLM,GenAI,Java,Aws,python

Additional Skills & Qualifications

• Ability to build full-stack applications using Java and/or Python with React and/or Angular.

• Strong AWS cloud-native development experience.

• Experience with CI/CD, automated testing, and Test-Driven Development.

• Hands-on experience building or integrating GenAI/LLM applications.

• Experience with AI agents, RAG, prompt engineering, model orchestration, or tool/function calling.

• Ability to work directly with business users and translate complex business problems into technical solutions.

• Strong written and verbal communication skills.

• Ability to explain complex technical…