AI Engineer

Blue Cross Blue Shield of Massachusetts

. Design and develop AI assistants using Vertex AI, including model selection, prompt engineering, grounding, retrieval-augmented generation, and agent orchestration .

Posted 11/2/2026full-timeBoston • Massachusetts • United StatesMid-LevelSenior💰 $140,310 - $171,490 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing AI assistants using Vertex AI and Google Cloud services, with a strong focus on AI/ML frameworks, agent orchestration, and responsible AI practices. Proficient in Python and experienced in building scalable, production-grade solutions while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Vertex AI DevelopmentGoogle Cloud Platform ServicesPython ProgrammingAI/ML FrameworksAgentic Application Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Assistant DesignPrompt EngineeringModel SelectionFunction Calling PatternsAPI DesignMicroservices ArchitectureData Privacy ComplianceMLOps PracticesEvaluation FrameworksTool Use Patterns

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

Google Cloud AI/ML SDKsVertex AI Agent BuilderBigQueryCloud FunctionsDialogflow CXLangChainTensorFlowPyTorchGitTerraform

Certifications & Qualifications

Google Cloud Certifications

Industry Keywords

AI/ML DevelopmentAgentic ArchitecturesRegulated IndustriesData PrivacyEmbedding-Based Retrieval

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformMicroservicesPythonPyTorchTensorflowTerraform

About the role

Key responsibilities & impact

Design and develop AI assistants using Vertex AI, including model selection, prompt engineering, grounding, retrieval-augmented generation, and agent orchestration
Build intelligent, multi-step AI agents using the Google Agent Development Kit (ADK)
Design agent architectures with tool use, sub-agents, callbacks, and session management
Develop and integrate applications using Google Cloud AI/ML SDKs
Design agentic architectures using sequential, loop, parallel, and custom agent hierarchies
Implement tool and function calling patterns connecting agents to enterprise APIs, databases, and external services
Implement responsible AI practices including safety filters, bias detection, guardrails, hallucination mitigation, and content moderation
Architect scalable, production-grade solutions using Vertex AI Agent Builder, Vertex AI Search, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, and other GCP services
Develop evaluation and monitoring frameworks measuring assistant quality, latency, cost, and user satisfaction
Collaborate with product managers, data engineers, and business stakeholders to translate requirements into AI-powered solutions
Evaluate emerging AI models, tools, and techniques and recommend adoption

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience
5+ years of experience in software engineering
At least 2+ years focused on AI/ML or LLM-based agentic development
Hands-on experience with Google Cloud Platform services, particularly BigQuery, Cloud Storage, Cloud Run, or Cloud Functions
Hands-on experience with Vertex AI Agent Builder, Vertex AI Search, or Dialogflow CX
Experience with Google Cloud SDKs, including Vertex AI SDK and Google Gen AI SDK, for model invocation, tuning, and deployment workflows
Strong proficiency in Python
Familiarity with ML/AI frameworks and libraries such as LangChain, LlamaIndex, TensorFlow, or PyTorch
Experience building agentic applications using LLMs, prompt engineering, function calling, embeddings, and retrieval-augmented generation
Understanding of API design, microservices architecture, and cloud-native development patterns
Familiarity with Git, CI/CD pipelines, and Infrastructure as Code such as Terraform or Cloud Build
Google Cloud certifications preferred
Exposure to multi-agent architectures, tool-use patterns, and agentic AI frameworks preferred
Experience with vector databases and embedding-based retrieval preferred
Knowledge of MLOps practices preferred
Experience in regulated industries and understanding of data privacy and compliance requirements preferred

Benefits

Comp & perks

Variable pay eligibility
Paid time off
Medical insurance
Dental insurance
Vision insurance
401(k)
Well-being benefits
Employee development investment and resources
Opportunities to forge a unique career path
Work/life balance support