Innovation Software Engineer - Hybrid or Remote

Genesis
10 is currently seeking an Innovation Principle Engineer for a contract to hire position with a Regional Financial Institution. This position can work on a hybrid or can work remotely in the footprint locations of Columbus, OH;
Minnetonka, MN;
Atlanta, GA:
Dallas, TX;
Detroit, MI;
Chicago, IL Compensation: $63.00 - $75.00 per hour, W2, based on qualifications

Position Overview:

This role supports the rapid delivery of innovation initiatives by designing and implementing AI-enabled applications and agentic solutions within Google Cloud. The Innovation Software Engineer will build application features, UI experiences, integrations, APIs, agent workflows, and deployment automation, with a strong focus on production implementation using Vertex AI, Gemini, and modern agent frameworks. This individual will work closely with senior engineers to rapidly bring solutions from concept through deployment while maintaining enterprise standards for security, reliability, governance, and observability.

Key Responsibilities:

Develop and enhance prototypes, proof-of-concept applications, and production-ready solutions, including UI screens, backend services, APIs, agent workflows, integrations, and automation scripts Design and implement AI-enabled and agentic application features using Google Cloud technologies, including Vertex AI and Gemini Build and deploy agent-based solutions using frameworks such as Google ADK, Agent Engine, Lang Graph, or equivalent technologies Deploy and operate AI-enabled applications and agent services using Google Cloud deployment patterns, ideally including Cloud Run, CI/CD, environment configuration, logging, monitoring, and observability Develop integrations with AI gateways or model-proxy layers supporting model routing, authentication, security controls, guardrails, and usage governance Implement grounding and Retrieval-Augmented Generation (RAG) patterns using technologies such as Vertex AI Search / Discovery Engine or comparable enterprise search and grounding capabilities Support model and AI-service governance, including token consumption, cost management, access controls, guardrails, and secure model usage Build and test integrations and workflow automations across systems to demonstrate business value and reduce manual effort Contribute to documentation, runbooks, and reusable implementation patterns to improve team speed and consistency Collaborate effectively across the team;

able to iterate rapidly, communicate progress, proactively remove blockers, and contribute to technical decisions Primary Requirements:
Bachelor's degree in Computer Science, Information Technology, Engineering or a related technical field 4+ years of experience in software engineering, application development, and innovative solution delivery Hands-on Google Cloud application development experience with demonstrated experience deploying solutions within GCP Production experience implementing AI-enabled applications using Vertex AI and Gemini; experience should extend beyond using Gemini or other GenAI tools solely as coding assistants Hands-on experience building and deploying agentic or multi-agent solutions using frameworks such as Google ADK, Agent Engine, Lang Graph, or comparable agent orchestration frameworks Hands-on experience building software applications, APIs, integrations, and backend services;

ability to independently drive initiatives with limited supervision Experience deploying applications or AI services using cloud-native patterns, preferably including Google Cloud Run Experience building UI screens and rapidly prototyping experiences using modern development tools, including AI-assisted development Experience writing scripts and automations to connect systems and streamline processes Comfort working in a fast-paced environment, progressing despite ambiguity and ability to independently lead development work streams from concept to execution Clear, structured verbal and written communication skills;

collaborative and proactive working style Desired

Skills:

Experience designing or integrating with an AI gateway, LLM gateway, or model-proxy platform, including model routing, authentication, access controls, and guardrails Experience implementing AI safety and security controls using Model Armor or comparable technologies Experience managing token usage, model consumption, observability, and AI-related cost governance Experience implementing grounding/RAG solutions using Vertex AI Search / Discovery…