Hiring Senior GCP/AI Engineer (Agentic AI Focus) in Phoenix

BrightSol AI is a fast-growing Phoenix-based scale-up specializing in the design and deployment of custom agentic AI solutions for regulated industries, including healthcare, logistics, and financial services. Operating across the United States and serving mid-market to enterprise clients, our team of 35 engineers and AI researchers focuses on building autonomous systems that reduce operational costs by an average of 40% for our customers, while ensuring full compliance with sector-specific data security standards. We are currently expanding our AI engineering team to support a 3x increase in client deployments planned for 2025.

We are hiring a Senior GCP/AI Engineer with specialized expertise in agentic AI to lead the design, deployment, and maintenance of end-to-end autonomous agent systems for our clients. In this role, you will work closely with our R&D team, client technical stakeholders, and DevOps engineers to build scalable, secure, and high-performance AI solutions that integrate seamlessly with existing enterprise infrastructure. You will be responsible for the full lifecycle of agentic AI deployments, from initial model fine-tuning to post-production monitoring and optimization.

Key responsibilities for this role include:
1. Design and deploy scalable agentic AI architectures on Google Cloud Platform, leveraging Vertex AI, Cloud Run, BigQuery, and Cloud Storage, ensuring 99.95% uptime and sub-200ms latency for real-time user interactions across all production deployments.
2. Develop, fine-tune, and optimize foundation models for client-specific use cases including document processing, workflow automation, and autonomous customer support, reducing inference costs by a minimum of 30% over 12 months via prompt optimization, model quantization, and efficient routing strategies.
3. Integrate deployed AI agents with client backend systems (ERP, CRM, ticketing platforms) via REST and GraphQL APIs, ensuring full compliance with HIPAA, GDPR, and SOC 2 security standards for all sensitive client data.
4. Implement comprehensive monitoring and observability pipelines for all AI agents using Prometheus, Grafana, and Cloud Monitoring, enabling incident identification and resolution within 15 minutes of detection, with a false positive rate on alerts below 5%.
5. Collaborate with QA engineers to design and implement automated test suites covering 95% of business use cases and failure scenarios for all AI agents, to be executed prior to every production deployment.
6. Train client technical support teams and project managers on the operation and basic maintenance of deployed AI agents, reducing AI-related ticket resolution time by 40% within 6 months of deployment.
7. Conduct ongoing research on emerging agentic AI frameworks and models (including LangChain, LlamaIndex, AutoGen, and open-source foundation models) and propose innovative implementations to improve the performance and reliability of existing client solutions.
8. Write detailed technical documentation for all architectures, models, and deployment processes to ensure operational continuity and reduce onboarding time for new team members by 50%.

Our work environment is hybrid, with 3 days per week spent at our Phoenix office and 2 days available for remote work, with flexibility for occasional travel to client sites across the US when required. Our engineering culture prioritizes autonomy and innovation: we run quarterly hackathons focused on experimental AI use cases, with a budget of $2,000 per employee annually for professional development and conference attendance. We avoid rigid hierarchical structures, with weekly 1:1 feedback sessions between engineers and their leads, and transparent sharing of company performance metrics with all staff.

To qualify for this role, you must have:
- A minimum of 5 years of professional experience in software engineering or AI engineering, including at least 2 years of hands-on experience building or deploying agentic AI systems or fine-tuning foundation models for production use cases.
- Expert-level proficiency with Google Cloud Platform, including hands-on experience deploying production-grade AI solutions using Vertex AI, Cloud Run, BigQuery, and Cloud IAM.
- Advanced proficiency in Python, with experience building production APIs and data pipelines; Java proficiency is a strong plus for integration with client enterprise backend systems.
- Hands-on experience with agentic AI frameworks including LangChain, LlamaIndex, AutoGen, or equivalent tools, with a portfolio of deployed agent use cases you can discuss.
- Experience with infrastructure monitoring tools (Prometheus, Grafana, Cloud Monitoring) and CI/CD pipelines (GitHub Actions, Cloud Build) for AI deployments.
- Familiarity with data security standards for regulated industries (HIPAA, GDPR, SOC 2) is a strong advantage.
- Strong ability to translate complex business requirements into clear, executable technical solutions, and to communicate technical concepts to non-technical stakeholders including client executives and operations teams.
- Prior experience in the healthcare, logistics, or financial services sectors is a plus.

The technical tools you will use regularly in this role include: GCP (Vertex AI, Cloud Run, BigQuery, Cloud IAM, Cloud Storage), Python, LangChain, LlamaIndex, AutoGen, Docker, Kubernetes, GitHub Actions, Prometheus, Grafana, SQL, REST APIs, GraphQL, and optionally Java for backend integration tasks.

Compensation for this role is competitive and aligned with senior-level AI engineering salaries in the Phoenix market: base salary ranges from $145,000 to $190,000 per year, depending on your years of specialized experience and technical proficiency. In addition to base salary, you will receive an annual performance bonus of up to 15% of your base salary, 90% coverage of health insurance premiums for you and your dependents, 20 days of paid time off plus 10 company-paid holidays per year, a hybrid work model with flexibility for occasional remote work outside of Phoenix with manager approval, a fully equipped home office stipend of $1,000 for hybrid employees, and a $2,500 annual professional development budget. We also offer a 5% annual profit-sharing contribution to your retirement account, and eligibility for full remote work after 1 year of employment with consistent performance reviews.

Career growth opportunities for this role are clearly defined: high-performing engineers can progress to Lead AI Engineer, AI Technical Project Manager, or Head of AI R&D within 2 to 3 years of joining the company. We cover all costs for attendance at major AI conferences including NeurIPS, ICML, and Google I/O, and you will have access to a dedicated senior mentor from our GCP engineering team to support your professional development. You will also have the opportunity to contribute to our open-source internal tools for agentic AI deployment, which we plan to release publicly in 2025.

Our hiring process for this role is structured to be transparent and efficient, with a total timeline of 2 to 3 weeks from application to offer:
1. Submit your application by emailing your resume to [email protected], along with a 2-3 sentence description of a successful agentic AI project you led or contributed to, and the impact it had on the end user or client.
2. A 30-minute initial phone screen with the Head of AI Engineering to discuss your experience and fit for the role.
3. A 48-hour at-home technical assessment: design a simple agentic AI architecture on GCP for a client ticket processing use case, including a short documentation of your technical choices and cost estimates.
4. A 1-hour technical interview with the AI engineering team to discuss your assessment, your past project experience, and your approach to solving common agentic AI challenges.
5. A 45-minute final interview with our Chief Technology Officer and HR Lead to discuss company culture, compensation expectations, and role expectations.
We commit to responding to all applicants within 5 business days of application submission, regardless of whether we are moving forward with your candidacy. If you have questions about the role or the hiring process, you can reach out to Ritik Sheth directly via LinkedIn or at the email address provided above.