5 days ago
Responsibilities
- Design and govern large-scale, secure, scalable, compliant AI/ML platforms with 99.99%+ availability requirements.
- Serve as the primary technical advisor for strategic client accounts and lead pre-sales solutioning, proposals, and stakeholder presentations.
- Spend 25–50% of the role on hands-on prototyping, production coding, framework design, and complex issue escalation.
- Architect multi-agent systems, autonomous workflow orchestration, memory and context management, and Model Context Protocol implementations.
- Establish LLMOps and MLOps standards covering prompt versioning, automated evaluation, CI/CD, drift detection, and production monitoring.
- Design AI security architectures aligned with HIPAA, HITRUST, GDPR, SOC 2, and OWASP LLM Top 10 requirements.
- Define reference architectures, conduct architectural reviews, manage technical debt, and mentor architects, senior engineers, and delivery teams.
Requirements
- 8+ years of progressive AI/ML engineering experience, including at least 3+ years in a technical leadership or architectural role.
- Deep expertise in system integration, legacy modernization, cloud-native design, API gateway architectures, and communicating complex architectural trade-offs.
- Mastery of statistical ML, deep learning architectures including Transformers, CNNs, and RNNs, and computer vision platforms.
- Proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Hands-on experience designing agentic systems and using frameworks such as LangGraph, CrewAI, AutoGen, LlamaIndex, or LangChain.
- Experience with Model Context Protocol, A2A communication, prompt engineering, LLM optimization techniques including PEFT, SFT, QLoRA, and DPO.
- Practical experience with vector databases such as Pinecone, Milvus, Qdrant, or OpenSearch.
- Experience designing end-to-end ML lifecycles including data ingestion, feature stores, registries, deployment, monitoring, and drift detection.
- Strong SQL and data transformation experience using BigQuery, Snowflake, Databricks, or Spark.
- Experience designing secure, compliant enterprise architectures aligned with frameworks such as SOC 2, GDPR, and ISO 27001.
- AWS or GCP Professional Cloud Architect and Machine Learning Engineer certifications are preferred.
- Publications, technical blogs, or conference presentations in agentic/generative AI or enterprise architecture are preferred.
- Exceptional technical reasoning, presentation, communication, stakeholder influence, and mentoring skills are required.
Benefits
- Opportunity to work at an AI-first digital transformation and engineering company with Fortune 500 clients and market disruptors.
- Exposure to current artificial intelligence, machine learning, data, and cloud technologies.
- Preferred location is Cambridge, Massachusetts; the role requires visits to client sites and travel to Cambridge/Pittsburgh.
Tech Stack
Apache SparkAWSDatabricksGoogle BigQueryGoogle CloudGoogle Cloud PlatformPythonPyTorchSnowflakeSQLTensorFlow
Categories
About Quantiphi
Quantiphi is an AI-first digital engineering and consulting firm that designs and implements machine learning, data, and cloud solutions for large enterprises across industries. Its teams build production systems—such as generative AI applications, computer vision, and predictive analytics—primarily on Google Cloud and other hyperscalers, delivered as professional services and managed solutions. Founded in 2013 and headquartered in Marlborough, Massachusetts, the company is privately held and a Google Cloud partner.