Senior AI/Machine Learning Engineer - Python | TheLoops

IFS•Palo Alto, CA

10d•$170,000 - $185,000

About The Position

As a Senior AI/ML Engineer, you will design, develop, and deploy enterprise-scale AI systems that power intelligent agents, copilots, and autonomous workflows. You will combine strong software engineering expertise with advanced AI/ML knowledge to build scalable, production-grade solutions leveraging LLMs, agent frameworks, retrieval systems, and modern cloud platforms. In this role, you will work closely with engineering, product, and domain experts to deliver high-quality AI solutions that drive measurable business value. You will contribute to the evolution of our AI platform by building reliable, secure, observable, and scalable systems while helping establish engineering best practices and sharing technical expertise with the broader team.

Requirements

5+ years of software engineering experience, including 2+ years building AI/ML-powered applications in production environments.
Strong proficiency in Python and experience designing backend systems and APIs.
Experience with LLMs, agent frameworks, RAG architectures, vector databases, embeddings, and AI orchestration platforms.
Hands-on experience with technologies such as OpenAI, Azure AI, Anthropic, Hugging Face, LangChain, LangGraph, Semantic Kernel, Pinecone, Weaviate, or equivalent platforms.
Solid understanding of software architecture, cloud-native development, microservices, and scalable system design.
Experience building and operating production applications in cloud environments.
Strong problem-solving, debugging, and performance optimization skills.
Effective communication and collaboration skills.

Nice To Haves

Experience building agentic AI systems, copilots, multi-agent workflows, or autonomous enterprise applications.
Experience with AI evaluation frameworks, LLM observability, AI governance, and responsible AI practices.
Experience with Azure, AWS, or GCP AI ecosystems.
Experience integrating enterprise platforms such as ERP, CRM, ITSM, HR, Finance, or Developer ecosystems.
Experience mentoring junior engineers or supporting technical onboarding.

Responsibilities

Design and implement scalable AI services and platform capabilities that support intelligent agents and enterprise workflows.
Build reusable SDKs, APIs, orchestration layers, and shared services that accelerate AI application development.
Contribute to architectural discussions and technical design reviews.
Develop solutions that meet requirements for reliability, observability, security, and scalability.
Design and implement production-grade solutions using LLMs, embeddings, RAG architectures, vector databases, memory systems, and agent orchestration frameworks.
Evaluate and integrate emerging AI technologies, foundation models, and agent frameworks where appropriate.
Develop prompt engineering approaches, evaluation strategies, and guardrails to improve quality, safety, and reliability.
Implement evaluation frameworks and AI quality metrics to measure system performance and business outcomes.
Optimize latency, accuracy, cost, and scalability of deployed AI systems.
Deliver complex AI initiatives from design through production deployment.
Apply best practices for testing, CI/CD, infrastructure automation, monitoring, and operational readiness.
Troubleshoot performance issues and conduct root-cause analysis across distributed AI services and integrations.
Ensure solutions align with enterprise requirements for governance, compliance, and security.
Collaborate with engineers, product managers, architects, and domain experts to translate business requirements into scalable technical solutions.
Provide technical guidance and share knowledge with team members.
Contribute to technical documentation, design reviews, and engineering best practices.
Support continuous improvement of development processes, tooling, and platform capabilities.