AI Engineer

Location: Hybrid - 4 days/week onsite | Must be willing to interview in person

Duration: Long-Term Contract

About the role

We are seeking a Senior AI Platform Engineer to design, build, and scale next-generation AI solutions for an Enterprise Data Platform on Google Cloud Platform (GCP). This is a highly technical, hands-on individual contributor role focused on developing production-grade multi-agent AI systems, AI-powered workflows, and developer-facing capabilities. The ideal candidate will combine deep software engineering expertise with practical experience building and operating LLM-based applications in production environments. This role requires ownership of solution architecture, hands-on development, technical leadership, and cross-functional collaboration to deliver scalable, secure, and observable AI solutions.

Responsibilities

• Design and implement multi-agent AI systems and agent orchestration frameworks.
• Evaluate architectural trade-offs, including:
  • Single-agent vs. multi-agent architectures
  • Retrieval-Augmented Generation (RAG) vs. fine-tuning approaches
  • Agent workflow design and orchestration strategies
• Contribute to Architecture Decision Records (ADRs) and technical design documentation.
• Define scalable, secure, and maintainable AI platform patterns.
• Develop and deploy production-grade AI applications and agentic workflows.
• Build solutions supporting:
  • Natural Language to SQL (NL-to-SQL)
  • Semantic search
  • Metadata enrichment
  • Intelligent automation workflows
• Implement AI guardrails, observability, monitoring, and evaluation frameworks.
• Leverage modern agent development tools and coding assistants.
• Develop backend services using Python and FastAPI.
• Build frontend experiences using Angular or React.
• Create chat interfaces, APIs, developer tooling, and user-facing AI experiences.
• Own end-to-end feature delivery from design through production deployment.
• Write high-quality, maintainable, and testable code.
• Lead technical reviews and establish engineering best practices.
• Perform root-cause analysis and troubleshoot complex AI agent failures.
• Serve as the team's technical expert for advanced AI and platform engineering challenges.
• Drive continuous improvements in reliability, scalability, and performance.
• Partner closely with Product Management, Data Engineering, and Platform Engineering teams.
• Participate in sprint planning, backlog refinement, and technical roadmap discussions.
• Mentor team members and promote knowledge sharing.
• Support onboarding and technical development of new engineers.

Requirements

• 5+ years of professional software engineering experience.
• Demonstrated hands-on coding expertise with modern application development practices.
• Experience building and operating AI-powered applications or LLM-based systems in production environments.
• Ability to interpret ambiguous business requirements and independently deliver robust, well-tested solutions.
• Experience designing scalable cloud-native applications.

Skills

• Artificial Intelligence and Expert Systems
• Large Language Models (LLMs)
• Agent-based AI architectures
• API development and microservices
• Python development
• FastAPI
• Frontend development using Angular or React
• Production software engineering and DevOps practices
• Experience building agent-based systems using frameworks such as:
  • Google Agent Development Kit (ADK)
  • CrewAI
  • LangGraph
  • Similar agent orchestration platforms
• Familiarity with agentic development tools and AI-assisted coding environments, including:
  • OpenCode
  • Claude Code
  • Comparable AI developer productivity tools

Preferred Qualifications

• Cloud & Platform Experience:
  • Google Cloud Platform (GCP)
  • Cloud-native application architecture
  • Platform engineering and AI infrastructure
• Machine Learning & AI:
  • Applied machine learning experience, including:
    • Embeddings
    • Classification
    • Clustering
    • Natural Language Processing (NLP)
  • Model evaluation and benchmarking
  • Experience implementing AI evaluation frameworks and quality metrics.
• Data & Governance:
  • Familiarity with data engineering principles
  • Enterprise data platforms
  • Metadata management
  • Data governance processes

Education

Bachelor’s or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.

Benefits

• Supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans.
• Employee Stock Purchase Program (ESPP).
• 401K program with company match after 12 months of tenure.
• Health Savings Account (HSA) on the HDHP plan.
• SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions.
• Corporate discount savings program and other discounts.
• On-demand training program.
• Access to certification prep and a library of technical and leadership courses/books/seminars after 6+ months of tenure.
• Certification discounts and perks to associations that include CompTIA and IIBA.
• Dedicated customer service team for consultants.
• Access to a certified Career Coach.

Schedule

Hybrid - 4 days/week onsite