Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.
We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.
Role Overview
The Innovations team at Genesys builds applications and agents on top of Genesys Cloud and ships them to enterprise customers through App Foundry. Think industry-specific agents built on the platform's agentic virtual agent capabilities, compliance tools, complementary platform integrations, and products that businesses use to orchestrate customer experiences every day. We operate more like a product studio than a traditional engineering organization.
We're hiring a full-stack engineer with financial services experience. This is someone who has worked with core financial systems of record and understands how they are used, along with the data constraints that come with them. You will bring that domain knowledge into building AI-powered CX applications. These are agents that can actually drive meaningful outcomes in financial services interactions because they are built by someone who understands the underlying systems.
You will work across the stack, including React frontends, backend services, and LLM integrations. You will be expected to take a messy customer problem, figure out what should be built, and get it into production.
The number one thing we hire for is drive. You do not wait for perfect requirements. You run experiments, measure results, and iterate.
Example projects
- A financial services AI agent built on Genesys Cloud's virtual agent platform that can handle account inquiries, claims status, payment processing, or loan servicing - integrating with core banking or insurance platforms and handing off to a human agent with full context when needed.
- A real-time compliance monitoring tool for regulated financial interactions - flagging disclosure gaps, TCPA violations, or missing disclosures and giving supervisors actionable options to coach or step into interactions.
- Evaluation infrastructure for our agent products in regulated environments - golden-set testing with domain-specific scenarios, adversarial conversation generation, and scoring that accounts for both quality and compliance.
Key Responsibilities
- Own features end-to-end: design, build, test, deploy, and iterate on AI agents and applications shipping to financial services customers.
- Build agentic systems that plan and act using tools and APIs, with attention to reliability, safety, and observability in production - especially in regulated environments where auditability matters.
- Bring working knowledge of financial services systems and data models to inform what we build and how we integrate.
- Work across the full stack: React/TypeScript, backend services (Java, Python, or Node), and LLM integration layers.
- Partner with solution consultants, product, and customers to understand the actual problem before writing code.
Required Qualifications
- 7+ years of professional software engineering, or equivalent demonstrated by shipped products.
- Meaningful experience in financial services - you've worked with or integrated against core platforms such as Fiserv, Temenos, FIS, Jack Henry, Guidewire, Duck Creek, or similar systems in banking, lending, insurance, payments, or wealth management. You understand the data models, regulatory constraints, and integration patterns of the domain.
- Full-stack fundamentals across frontend, backend, and APIs. TypeScript/JavaScript plus Java, Python, or Node.
- Hands-on experience building with LLMs - tool calling, structured outputs, retrieval/RAG, evaluation. Production preferred, serious side projects count.
- Comfortable with agentic patterns: multi-step reasoning, autonomous tool use, structured planning, and the failure modes that come with giving an LLM real agency.
- Working familiarity with AWS - you've deployed and operated services there. Experience with Lambda, ECS/Fargate, Bedrock, or similar is a plus.
- High ownership: you self-start, you ship, you figure things out.
Preferred Qualifications
- Experience building customer-facing applications in banking, insurance, or wealth management - especially anything involving real-time interaction handling or servicing workflows.
- Experience in customer service, contact center, or CX domains, especially AI-oriented systems like Sierra, Decagon, or Kore.AI.
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