Hiring GCP/AI Engineer (Agentic AI) in Phoenix

BrightSol is a fast-growing technology company specializing in artificial intelligence and cloud computing solutions, founded in 2018 and headquartered in Phoenix, Arizona. We work with mid-sized and large enterprises across the healthcare, finance, and logistics sectors in the United States, helping them automate critical processes, reduce operational costs, and improve decision-making through custom AI and cloud deployments. With a team of 120 employees across three offices (Phoenix, Austin, and New York), we recently closed a $25M Series B funding round to accelerate the development of our agentic AI product line, which is already used by 40+ clients to manage supply chain operations, patient scheduling, and fraud detection. Our culture is built on autonomy, collaboration, and continuous learning: we give our teams the space to experiment, share ideas freely, and grow their skills without bureaucratic barriers.

We are currently hiring a Senior GCP/AI Engineer specialized in Agentic AI to join our cloud and AI team based in Phoenix. In this role, you will be responsible for designing, deploying, and maintaining autonomous AI agents for our logistics clients, using Google Cloud Platform (GCP) services and cutting-edge generative AI models. You will work closely with our backend Java development team, QA automation engineers, and technical support teams to ensure our AI solutions are reliable, scalable, and aligned with client requirements. This is a hands-on role for an engineer who is passionate about building practical AI applications that deliver measurable business value, not just theoretical research.

Your key responsibilities will include:
1. Design, deploy, and maintain autonomous AI agents on GCP infrastructure, using Vertex AI, BigQuery, and Cloud Functions, to automate demand forecasting and inventory optimization processes for our logistics clients, achieving a minimum prediction accuracy rate of 95% across all deployed models.
2. Optimize the performance of generative AI and agentic AI models (including Llama 3, Gemini, and Mistral) deployed on GCP, reducing inference latency by 30% within the first 6 months of deployment, while adhering to client-defined cloud cost constraints.
3. Build and maintain CI/CD pipelines for AI model and agent deployments, using Cloud Build, Artifact Registry, and Terraform, to reduce new model version deployment time by 40% compared to our current processes, while ensuring zero downtime during updates.
4. Collaborate with backend Java and QA automation teams to integrate AI agents into client-facing applications, resolving 90% of integration-related incidents within 4 business hours of being reported, to meet service level agreement (SLA) targets.
5. Conduct security and compliance audits of GCP AI deployments, ensuring full alignment with HIPAA regulations for healthcare clients and PCI DSS standards for finance clients, achieving a 100% compliance rate during all client and regulatory audits.
6. Train technical support teams and project managers on the functionality and troubleshooting of deployed AI agents, reducing AI-related support requests by 25% within the first 3 months after each deployment.
7. Stay up to date with the latest advancements in agentic AI and GCP services, proposing at least 2 new features or process improvements per quarter that are adopted into our company's product offerings.

Our work environment is hybrid: you will spend 3 days per week in our Phoenix office located in the Midtown district, which features modern coworking spaces, a fully equipped gym, free catered lunches twice a week, and quiet rooms for focused work. The remaining 2 days can be worked remotely, with flexible core hours between 9am and 4pm to accommodate team meetings and collaboration. Our AI team is made up of 8 engineers and data scientists, with daily 15-minute stand-ups, weekly code review sessions, and Friday afternoon knowledge-sharing workshops where team members present recent projects or learnings from conferences. We do not enforce a rigid hierarchy: junior team members are encouraged to share ideas directly with senior leadership, and all employees can dedicate 10% of their work time to personal AI-related projects, with the best ideas receiving funding and resources to be turned into official company products.

To be successful in this role, you will need:
- A minimum of 5 years of professional experience in a cloud engineering or AI engineering role, with at least 2 years of specific experience building and deploying agentic AI solutions on GCP.
- Mastery of core GCP services including Vertex AI, BigQuery, Cloud Functions, Cloud Build, and Terraform for infrastructure as code.
- Hands-on experience with generative AI and agentic AI frameworks including LangChain, LlamaIndex, and at least one of the following model families: Llama, Gemini, or Mistral.
- Proficiency in Python and Java, with experience building production-grade AI applications and backend services.
- Experience with CI/CD tools for AI deployments, including Cloud Build, Jenkins, or GitLab CI.
- Familiarity with healthcare (HIPAA) and finance (PCI DSS) compliance requirements for cloud and AI deployments is a strong plus.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders including clients and project managers.
- A bachelor's degree in Computer Science, Data Science, or a related technical field, or equivalent professional experience.

In terms of compensation and benefits, we offer a highly competitive package aligned with senior AI engineering market rates in the Phoenix metro area:
- Annual base salary between $145,000 and $180,000, depending on your years of relevant experience and technical expertise.
- Annual performance bonus of up to 15% of your base salary, tied to team and project success metrics.
- 90% coverage of health insurance premiums for you and your dependents, including dental and vision coverage.
- 25 days of paid time off per year, plus 10 additional paid sick days, with no accrual caps.
- 5% annual profit-sharing contribution to your retirement account, in addition to any employer 401(k) match.
- $2,000 annual professional development budget, fully covered by the company, to use for certifications, conferences, or courses (we cover costs for Google Cloud certifications, NeurIPS, Google I/O, and other relevant events).
- Fully equipped workstation: you can choose between a MacBook Pro or Dell XPS laptop, plus an external monitor, keyboard, and mouse, with full licenses for all required development tools.
- Flexible work schedule: you can adjust your daily start and end times between 7am and 7pm, as long as you are available for core team meetings between 9am and 4pm.
- No extended probation period: your probation period will be 3 months, in line with Arizona state labor laws.

We prioritize internal growth and career development: after 2 years in this role, you will be eligible to apply for either a Lead AI Engineer position (managing a team of 3-4 junior and mid-level engineers) or a GCP Cloud Architect role (responsible for designing cloud infrastructure for all company clients). We cover 100% of the cost of relevant professional certifications and exam fees, and you will have the opportunity to contribute to internal R&D projects on agentic AI, with the possibility of having your work published at industry conferences or integrated into our commercial products.

Our recruitment process is designed to be transparent and efficient, with a total duration of no more than 2 weeks:
1. A 30-minute initial phone call with our recruitment manager to discuss your background, expectations, and alignment with the role.
2. A 2-hour at-home technical assessment, where you will build a simple AI agent on GCP using Vertex AI and LangChain, then present your technical choices and tradeoffs.
3. A 1-hour technical interview with the cloud and AI engineering team, to discuss your assessment, past project experience, and how you approach problem-solving for complex AI deployment challenges.
4. A 30-minute final interview with our Chief Technology Officer and HR lead, to discuss compensation, career growth opportunities, and answer any remaining questions.

If you are interested in this role, submit your CV and LinkedIn profile to [email protected], with the subject line "Candidature GCP/AI Engineer Agentic AI - [Your Full Name]". We respond to all applications within 5 business days, and if your profile is selected, we will contact you within 7 days to schedule the first step of the process. We look forward to hearing from you and potentially welcoming you to the BrightSol team.