Job Summary: • Partner with business stakeholders across Prosperity to understand workflows and pain points, and proactively identify areas where agentic AI can drive meaningful improvement. • Design, build, and deploy AI agents that automate or augment business processes — from initial concept through production deployment. • Work full-stack: build the agent logic/orchestration as well as the surrounding application layer, integrations, APIs, and data pipelines needed to make an agent usable in a real workflow. • Rapidly prototype agentic solutions, validate them with business users, and iterate quickly based on feedback. • Evaluate and select appropriate agent frameworks, tooling, and LLM/model choices for each use case. • Partner with platform/architecture teams to ensure agents are secure, scalable, auditable, and aligned with enterprise AI governance standards. • Own technical delivery of assigned use cases end-to-end — discovery, build, deployment, and post-launch monitoring/tuning. • Act as a trusted technical voice for agentic AI within Prosperity, educating business partners on realistic capabilities and limitations. • Identify patterns across use cases and feed reusable agent components/frameworks back to the broader engineering organization.
Required Skills & Experience: • Strong full-stack software engineering background (front-end, back-end, APIs, data layer) with hands-on coding ability — this is a builder role, not an advisory one. • Direct, hands-on experience building AI agents or agentic workflows (e.g., using LLM orchestration frameworks, tool-calling/function-calling, RAG pipelines, or multi-agent systems). • Demonstrated ability to independently identify business opportunities for AI/agentic involvement — not just execute a pre-defined technical spec. • Comfort working directly with business stakeholders to scope ambiguous problems and translate them into working solutions. • Experience with cloud platforms (AWS/Azure/GCP) and modern data/AI tooling. • Strong communication skills — able to explain agentic AI concepts, tradeoffs, and limitations to non-technical business partners. • Comfort with fast iteration cycles and evolving requirements typical of emerging-technology initiatives. • Prior experience in a Forward Deployed Engineer, Applied AI Engineer, or Solutions Engineer role. • Experience with agent frameworks/tooling such as LangChain, LangGraph, AutoGen, Semantic Kernel, or similar. • Domain knowledge in Wealth Management, Retirement Services, or broader financial services. • Experience with enterprise AI governance, model risk, or responsible AI practices in a regulated industry. • Prior startup, consulting, or client-facing delivery experience.
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At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.This position's pay range is $52.00/hr - $57.00/hr.
