Lead the architecture, development, and implementation of an enterprise-grade agentic AI orchestration platform. Build reusable AI components and intelligent agents using Claude, LangGraph, RAG, vector databases, MCP, prompt engineering, and multi-agent workflows. Develop scalable FastAPI APIs, ensure AI security and responsible AI practices, support enterprise or regulated data environments, and provide technical leadership across architecture and engineering efforts.
This is a remote position.
We are seeking a highly experienced Senior AI/ML Engineer / Architect to lead the design, development, and implementation of an enterprise-grade Agentic AI orchestration platform. The platform will leverage Claude 3.5 Sonnet/Opus, LangGraph, advanced prompt engineering, RAG, vector databases, MCP, and multi-agent workflows to create reusable AI components and intelligent agents based on a modular “Bricks” / multi-node architecture.
Requirements
- 10+ years of overall software engineering / AI/ML experience for Senior AI/ML Engineer / Architect positions.
- Strong production experience with LLM-based applications.
- Strong Python development background.
- Hands-on Claude API experience.
- Strong LangGraph/LangChain experience.
- Experience designing agentic AI architectures.
- Experience with RAG and vector databases.
- Strong prompt-engineering skills.
- Experience building scalable APIs using FastAPI.
- Strong understanding of AI security and responsible AI.
- Experience working with enterprise or regulated data environments.
- Strong architecture and technical leadership capabilities.
- Excellent communication and problem-solving skills.
Similar Jobs
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software
Design and build scalable AWS cloud, Big Data, and machine-learning infrastructure for AI-powered Workforce Management. Lead distributed data pipeline and workflow-orchestration projects from architecture through production, improve reliability, scalability, observability, security, and cost efficiency, and develop automated testing. Collaborate across engineering, data science, product, and platform teams while influencing architecture, owning major initiatives, reviewing designs and code, and mentoring junior engineers.
Top Skills:
AirflowSparkAPIsAuroraAWSAws BatchAws CdkCi/CdCloudFormationCloudwatchDynamoDBEcsEmrFargateJavaKubeflowLambdaMachine LearningMetaflowNew RelicOpentelemetryPythonS3ScalaSqsStep FunctionsTerraform
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.
Top Skills:
AgentsAi InfrastructureEvaluation SystemsLlmsRetrieval Architectures
Information Technology • Cybersecurity
Lead development of back-end systems and end-to-end data/ML pipelines, build and deploy generative AI workflows, design and consume performant APIs, contribute to AI/ML architecture, mentor engineers, and communicate progress to leadership.
Top Skills:
GraphQLGrpcJwtKubernetesMlopsMongoDBMySQLOauthPostgresPythonRest
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



