Innovation Software Engineer - Hybrid

Genesis10•Columbus, OH

3h•Hybrid

About The Position

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.

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, LangGraph, 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 workstreams from concept to execution
Clear, structured verbal and written communication skills; collaborative and proactive working style

Nice To Haves

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 Engine or comparable enterprise retrieval platforms
Experience deploying AI applications within regulated or highly controlled environments, including exposure to VPC Service Controls (VPC-SC), private networking, DLP, or similar security patterns
Hands-on experience developing applications and automation using one or more modern programming or scripting languages such as Java, Python, TypeScript/JavaScript, or similar
Experience with AWS Bedrock, Azure OpenAI, or other cloud AI platforms is beneficial when combined with demonstrated hands-on Google Cloud AI deployment experience
Strong collaboration and communication skills, ability to drive work proactively, and positive track record of reliability and delivery

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, LangGraph, 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

Benefits

Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years
The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years
Access to an experienced, caring recruiting team (more than 7 years of experience, on average)
Behavioral Health Platform
Medical, Dental, Vision
Health Savings Account
Voluntary Hospital Indemnity (Critical Illness & Accident)
Voluntary Term Life Insurance
401K
Sick Pay (for applicable states/municipalities)
Commuter Benefits (Dallas, NYC, SF, and Illinois)