Senior AI Engineer

The Muse

Senior AI Engineer delivering innovative AI solutions while collaborating with AI & Engineering team at PURE. Focus on transforming technology platforms and driving operational performance through AI.

Posted 7/24/2026full-timeWhite Plains • New York • 🇺🇸 United StatesSenior💰 $85,000 - $105,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and deploying AI solutions, particularly with LLMs and cloud-native patterns on AWS. Proficient in software engineering practices, including clean code development, CI/CD integration, and implementing governance controls in AI systems.

Highest-signal resume keywords

AI/ML Systems DevelopmentAWS Cloud ServicesPython ProgrammingLLM Prompt EngineeringContainer Orchestration

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI Solutions DevelopmentSoftware EngineeringPrompt EngineeringFeature PipelinesModel ServingContainerized ApplicationsServerless ApplicationsData GovernanceCI/CD IntegrationSDLC Knowledge

Soft Skills

Team CollaborationIterative DevelopmentProblem Solving

Tools & Technologies

AWS AgentCore GatewayDatabricksFastAPIDockerGitHub CopilotClaude CodeOpenAI CodexTerraformLangChainAWS SAM

Industry Keywords

AI SolutionsMachine LearningGovernance ControlsData PrivacyRegulatory Compliance

Tech Stack

Tools & technologies

AWSCloudDockerJavaPythonSDLCTerraform

About the role

Key responsibilities & impact

Join our AI & Engineering team in transforming technology platforms, driving innovation, and making a significant impact on our members' success.
You will work alongside talented professionals reimagining and re-engineering operations and processes that are critical to our business — from underwriting and claims to member experience and risk management.
Build & Deploy AI Solutions Partner with the Lead AI Solutions Architect and AI Data Engineer to design, build, and deploy secure, scalable AI solutions: APIs, services, pipelines, agents, containers, and serverless functions that meet availability, performance, and security requirements.
Deploy AI workloads primarily using cloud-native patterns, including AWS ECS-based containerized applications.
Build and operationalize LLM-enabled products including copilots, knowledge assistants, summarization engines, policy Q&A tools, and agentic workflows using Claude Code, OpenAI Codex, GitHub Copilot, AWS AgentCore Gateway, AWS AgentCore Harness, Databricks, and comparable LLM platforms.
Implement RAG, knowledge base, and document intelligence patterns end-to-end: ingestion, chunking, embeddings, vector and hybrid search, retrieval evaluation, and telemetry.
Deliver governed data and features for ML and GenAI — curated datasets, feature pipelines, and feature serving — supporting both training workflows and real-time inference with consistency, caching, backfill support, and latency SLOs.
Apply thoughtful prompt and context patterns, tool/function calling, reusable agent skills, and agentic orchestration patterns.
Ensure AI outputs are auditable, explainable, and compliant with applicable regulatory requirements (SOC 2, NAIC, GDPR).

Requirements

What you’ll need

5+ years of professional software engineering experience, with at least 1 year building and operating AI/ML systems in production.
Proven hands-on experience with LLMs: prompt engineering, RAG pipelines, fine-tuning or adapting open-source models, function/tool calling, agent orchestration, and working with Claude, OpenAI/Codex, Gemini, or comparable models via API..
Experience building and shipping agentic AI systems, multi-step agents, tool-use orchestration, reusable agent skills, autonomous workflow automation, and governed enterprise integrations in a production environment.
Experience with AWS AgentCore Gateway, AWS AgentCore Harness, LangChain, LangGraph, or comparable agent frameworks is highly valuable..
Strong Python engineering skills; ability to write clean, maintainable, production-grade code with FastAPI or similar frameworks, and package AI capabilities as APIs, services, workers, or containerized applications..
Experience with AI/ML infrastructure: Databricks-based AI/ML workflows, knowledge bases, vector or hybrid search, feature pipelines, model serving patterns, container orchestration, Docker, and cloud-native deployment Familiarity with cloud-native AI workloads on AWS — including cost governance and performance tuning at scale.
Experience implementing trust, safety, and governance controls in AI systems: PII handling, content filtering, access controls, and auditability.
Comfort working in a delivery-oriented team: you ship, you measure, you iterate.
Hands-on experience with AI-assisted software engineering tools such as Claude Code, OpenAI Codex, GitHub Copilot, or comparable developer productivity platforms.
Experience creating reusable AI agent artifacts such as skill files, tool definitions, prompt templates, system instructions, evaluation datasets, and guardrail patterns.
Experience with building reusable Github Workflow and make AI solutions part of the CI/CD.
Knowledge and experience with the Software Development Life Cycle (SDLC), including both low-code/no-code platforms and traditional application development using Java/Python.
Experience in building Serverless applications in AWS using AWS SAM Knowledge and experience with Terraform.

Benefits

Comp & perks

Opportunities to stretch and grow: your professional and personal development matters to us.
We’re committed to providing experiences through on-the-job learning and professional development that increase your impact and rewards.
Clarity and kindness: you can rely on us to be open, honest and supportive, offering clarity on what success looks like.
Support in good times and bad: we believe in showing up for each other consistently, not only when it’s easy.
You can expect a thoughtful partner, even when we disagree.
A community that cares: we are committed to sustaining a community in which each person feels cared for as an individual. We lift each other up, celebrate wins together and support one another through challenges in work and life.