Senior Agentic AI Platform Engineer

This is a fully remote position, open to applicants in Connecticut.

📋 Description

• Design, develop, and sustain reusable platform components, accelerators, pipelines, agent harnesses, and shared services within Google Vertex AI, ServiceNow AI, Databricks, and Claude-based ecosystems.

• Create foundational enterprise AI capabilities such as RAG frameworks, vector-enabled architectures, evaluation frameworks, orchestration services, model integration patterns, and reusable engineering accelerators.

• Take ownership of shared platform capabilities through architecture, versioning, production hardening, performance optimization, adoption support, and continuous improvement.

• Implement secure-by-design strategies encompassing AI governance, access controls, data privacy protections, prompt injection safeguards, resiliency mechanisms, failover strategies, and graceful degradation.

• Collaborate with AI Solutions Architects, Product Delivery, Architecture, Security, and Operations teams to promote adoption and provide onboarding and technical assistance.

• Articulate architectural decisions and technical trade-offs to engineering teams and senior management.

• Provide mentorship to interns and contractors, offering technical leadership and guidance on engineering best practices.

⛳️ Requirements

• A minimum of 5 years of experience in building AI/ML platforms, developer platforms, shared engineering frameworks, or enterprise-scale software solutions with growing technical responsibility.

• At least 4 years of experience in developing reusable platform capabilities, accelerators, tooling, or shared services utilized across various engineering teams in enterprise settings.

• A minimum of 3 years of practical experience in creating production solutions on Google Vertex AI, Azure AI, ServiceNow AI, Databricks, or comparable cloud AI platforms.

• At least 2 years of experience in designing and implementing RAG, agentic AI architectures, vector search solutions, and large language model integrations.

• A minimum of 2 years of experience designing secure, scalable, and highly available distributed systems while applying best practices in AI governance, privacy, resiliency, and operational reliability.

• Strong expertise in full-stack and Python engineering, including production-grade development, API and microservice architecture, FastAPI, Docker, pytest, CI/CD, and cloud-native application design.

• Experience in building agentic AI solutions utilizing Claude or similar large language models, tool use, function calling, agent orchestration, MCP, and multi-step reasoning patterns.

• Knowledge of prompt engineering, context engineering, retrieval engineering, chunking strategies, embedding models, vector databases like pgvector, retrieval tuning, reranking, caching strategies, and evaluation frameworks.

• Familiarity with document ingestion and parsing frameworks such as Docling or Unstructured; experience with SQL, schema migration tools, ETL pipelines, and bronze, silver, and gold data architectures.

• Experience in supporting healthcare, pharmacy, cybersecurity, AIOps, or other regulated environments; exposure to MLOps, LLMOps, Cloud SQL, Cloud Functions, and IAM.

• Bachelor’s degree from an accredited university or equivalent work experience (High School diploma plus 4 years of relevant experience).

🏝️ Benefits

• CVS Health bonus, commission, or short-term incentive program in addition to base salary.

• Medical coverage.

• Dental coverage.

• Vision coverage.

• Paid time off.

• Retirement savings options.

• Wellness programs.

• Additional resources supporting physical, emotional, and financial well-being.